{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\lSMS ISA\dofile\Submission\Table1_Figures.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 5 Apr 2024, 10:56:16
{txt}
{com}. use  NER_panel_data.dta, clear
{txt}
{com}. gen country=1
{txt}
{com}. append using NIGERIA_panel_data.dta
{txt}
{com}. replace country=2 if country ==.
{txt}(18,592 real changes made)

{com}. 
. append using ETHIOPIA_panel_data.dta
{txt}
{com}. replace country=3 if country ==.
{txt}(13,511 real changes made)

{com}. 
. append using UGA_panel_data.dta
{txt}
{com}. replace country=4 if country ==.
{txt}(20,313 real changes made)

{com}. 
. append using TZA_panel_data.dta
{txt}
{com}. replace country=5 if country ==.
{txt}(21,117 real changes made)

{com}. 
. append using MWI_panel_data.dta
{txt}
{com}. replace country=6 if country ==.
{txt}(9,163 real changes made)

{com}. 
. xtset HHID_panel year
{res}{txt}{col 8}panel variable:  {res}HHID_panel (unbalanced)
{txt}{col 9}time variable:  {res}{col 25}year, 2008 to 2019, but with gaps
{txt}{col 17}delta:  {res}1 unit
{txt}
{com}. 
. label define country 1 "Niger" 2 "Nigeria" 3 "Ethiopia" 4 "Uganda" 5 "Tanzania" 6 "Malawi"
{txt}
{com}. label values country country
{txt}
{com}. ********************************************************************************
. *                               Table 1                                        *
. ********************************************************************************
. preserve
{txt}
{com}. mat Y = J(100,5,.)
{txt}
{com}. local tt "  hdd9 hdd9_own hdd9_purchase hdd9_gift  own_value_share purchase_value_share other_value_share"
{txt}
{com}. foreach x of varlist    own_value_share purchase_value_share other_value_share other_crop{c -(}
{txt}  2{com}. replace `x'=`x'*100
{txt}  3{com}. {c )-}
{txt}(50,660 real changes made)
(75,695 real changes made)
(34,998 real changes made)
(17,232 real changes made)

{com}. 
. local g 1
{txt}
{com}. foreach var of varlist `tt'  {c -(}
{txt}  2{com}. ttest `var'=0
{txt}  3{com}. mat Y[`g',1] = r(mu_1)
{txt}  4{com}. local g=`g'+1
{txt}  5{com}. mat Y[`g',1] = r(sd_1)
{txt}  6{com}. local g=`g'+1
{txt}  7{com}. 
. {c )-}

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
    hdd9 {c |}{res}{col 12} 89,742{col 22} 5.663669{col 34}  .005853{col 46} 1.753371{col 58} 5.652197{col 70} 5.675141
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}hdd9{txt})                                             t = {res}967.6583
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
hdd9_own {c |}{res}{col 12} 82,550{col 22} 1.671157{col 34} .0056343{col 46} 1.618817{col 58} 1.660114{col 70}   1.6822
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}hdd9_own{txt})                                         t = {res}296.6047
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   82549

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
hdd9_p~e {c |}{res}{col 12} 82,550{col 22} 4.502047{col 34} .0077612{col 46} 2.229922{col 58} 4.486835{col 70} 4.517259
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}hdd9_purchase{txt})                                    t = {res}580.0680
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   82549

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
hdd9_g~t {c |}{res}{col 12} 82,550{col 22} .6361478{col 34} .0035368{col 46} 1.016177{col 58} .6292157{col 70} .6430799
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}hdd9_gift{txt})                                        t = {res}179.8653
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   82549

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
own_va~e {c |}{res}{col 12} 78,003{col 22} 33.13994{col 34} .1200212{col 46} 33.52074{col 58}  32.9047{col 70} 33.37518
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}own_value_share{txt})                                  t = {res}276.1174
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   78002

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
purcha~e {c |}{res}{col 12} 78,003{col 22} 59.12904{col 34} .1240404{col 46} 34.64327{col 58} 58.88593{col 70} 59.37216
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}purchase_value_share{txt})                             t = {res}476.6917
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   78002

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
other_~e {c |}{res}{col 12} 78,003{col 22} 7.731016{col 34} .0603413{col 46} 16.85272{col 58} 7.612747{col 70} 7.849284
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}other_value_share{txt})                                t = {res}128.1215
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   78002

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000
{txt}
{com}. 
. matrix rownames Y = hdd9 sd hdd9_own sd hdd9_purchase sd hdd9_gift sd own_value_share sd purchase_value_share sd other_value_share sd
{txt}
{com}. 
. matrix colnames Y =  % sd
{txt}
{com}. 
. matrix list Y
{res}
{txt}Y[100,5]
                      %         sd         sd         sd         sd
        hdd9 {res} 5.6636692          .          .          .          .
{txt}          sd {res} 1.7533706          .          .          .          .
{txt}    hdd9_own {res} 1.6711569          .          .          .          .
{txt}          sd {res} 1.6188167          .          .          .          .
{txt}hdd9_purch~e {res} 4.5020472          .          .          .          .
{txt}          sd {res} 2.2299219          .          .          .          .
{txt}   hdd9_gift {res} .63614779          .          .          .          .
{txt}          sd {res} 1.0161767          .          .          .          .
{txt}own_value_~e {res} 33.139941          .          .          .          .
{txt}          sd {res} 33.520736          .          .          .          .
{txt}purchase_v~e {res} 59.129044          .          .          .          .
{txt}          sd {res} 34.643271          .          .          .          .
{txt}other_valu~e {res} 7.7310156          .          .          .          .
{txt}          sd {res} 16.852723          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
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{reset}
{com}. frmttable using Table_1_Whole.doc, replace  statmat(Y) ctitle("", "mean", "sd") sdec(2)
{res}
{txt}{center:{hline 41}}
{center:{txt}{lalign 22:}{txt}{center 7:mean}{txt}{center 4:sd}{txt}{center 2:}{txt}{center 2:}{txt}{center 2:}}
{txt}{center:{hline 41}}
{center:{txt}{lalign 22:hdd9}{res}{center 7:5.66}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:1.75}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_own}{res}{center 7:1.67}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:1.62}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_purchase}{res}{center 7:4.50}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:2.23}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_gift}{res}{center 7:0.64}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:1.02}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:own_value_share}{res}{center 7:33.14}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:33.52}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:purchase_value_share}{res}{center 7:59.13}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:34.64}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:other_value_share}{res}{center 7:7.73}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:16.85}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{txt}{center:{hline 41}}


{com}. restore
{txt}
{com}. 
. 
. 
. 
. 
. preserve
{txt}
{com}. keep if country==3|country==6
{txt}(67,068 observations deleted)

{com}. mat Y = J(100,5,.)
{txt}
{com}. local tt "  hdd9 hdd9_own hdd9_purchase hdd9_gift  own_value_share purchase_value_share other_value_share"
{txt}
{com}. foreach x of varlist    own_value_share purchase_value_share other_value_share other_crop{c -(}
{txt}  2{com}. replace `x'=`x'*100
{txt}  3{com}. {c )-}
{txt}(12,150 real changes made)
(17,527 real changes made)
(8,847 real changes made)
(6,092 real changes made)

{com}. 
. 
. local g 1
{txt}
{com}. foreach var of varlist `tt'  {c -(}
{txt}  2{com}. ttest `var', by(country)
{txt}  3{com}. mat Y[`g',1] = r(mu_1)
{txt}  4{com}. mat Y[`g',2] = r(mu_2)
{txt}  5{com}. local g=`g'+1
{txt}  6{com}. mat Y[`g',1] = r(sd_1)
{txt}  7{com}. mat Y[`g',2] = r(sd_2)
{txt}  8{com}. local g=`g'+1
{txt}  9{com}. 
. {c )-}

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12} 13,511{col 22} 4.424691{col 34} .0134154{col 46} 1.559364{col 58} 4.398395{col 70} 4.450987
  {txt}Malawi {c |}{res}{col 12}  9,163{col 22} 6.241187{col 34} .0182565{col 46} 1.747577{col 58} 6.205401{col 70} 6.276974
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 22,674{col 22} 5.158772{col 34} .0123845{col 46} 1.864842{col 58} 5.134498{col 70} 5.183047
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-1.816496{col 34} .0221678{col 58}-1.859947{col 70}-1.773046
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res}-81.9429
{txt}Ho: diff = 0                                     degrees of freedom = {res}   22672

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12} 10,583{col 22} 1.388548{col 34} .0128209{col 46} 1.318933{col 58} 1.363416{col 70} 1.413679
  {txt}Malawi {c |}{res}{col 12}  9,155{col 22} 1.703332{col 34} .0164654{col 46} 1.575437{col 58} 1.671056{col 70} 1.735607
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 19,738{col 22} 1.534553{col 34} .0103355{col 46} 1.452058{col 58} 1.514294{col 70} 1.554811
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.3147838{col 34} .0206044{col 58}-.3551702{col 70}-.2743975
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res}-15.2775
{txt}Ho: diff = 0                                     degrees of freedom = {res}   19736

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12} 10,583{col 22} 3.075404{col 34}  .019111{col 46} 1.966018{col 58} 3.037943{col 70} 3.112865
  {txt}Malawi {c |}{res}{col 12}  9,155{col 22} 4.995631{col 34} .0241492{col 46} 2.310642{col 58} 4.948293{col 70} 5.042969
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 19,738{col 22} 3.966055{col 34} .0166406{col 46}  2.33787{col 58} 3.933438{col 70} 3.998672
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-1.920227{col 34} .0304416{col 58}-1.979895{col 70}-1.860559
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res}-63.0790
{txt}Ho: diff = 0                                     degrees of freedom = {res}   19736

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12} 10,583{col 22} .2671265{col 34} .0062237{col 46} .6402544{col 58} .2549269{col 70} .2793261
  {txt}Malawi {c |}{res}{col 12}  9,155{col 22} 1.216166{col 34} .0130742{col 46} 1.250965{col 58} 1.190538{col 70} 1.241794
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 19,738{col 22} .7073158{col 34} .0076978{col 46} 1.081475{col 58} .6922276{col 70} .7224041
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.9490395{col 34} .0138797{col 58}-.9762449{col 70}-.9218342
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res}-68.3762
{txt}Ho: diff = 0                                     degrees of freedom = {res}   19736

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12}  9,864{col 22} 42.79573{col 34} .3977118{col 46} 39.49981{col 58} 42.01614{col 70} 43.57533
  {txt}Malawi {c |}{res}{col 12}  8,567{col 22} 31.10631{col 34} .3390958{col 46} 31.38606{col 58}  30.4416{col 70} 31.77102
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 18,431{col 22} 37.36232{col 34} .2683069{col 46} 36.42557{col 58} 36.83641{col 70} 37.88823
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 11.68942{col 34} .5310261{col 58} 10.64856{col 70} 12.73028
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res} 22.0129
{txt}Ho: diff = 0                                     degrees of freedom = {res}   18429

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12}  9,864{col 22} 50.03839{col 34} .3987371{col 46} 39.60164{col 58} 49.25679{col 70}    50.82
  {txt}Malawi {c |}{res}{col 12}  8,567{col 22} 55.89028{col 34} .3626219{col 46} 33.56359{col 58} 55.17945{col 70}  56.6011
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 18,431{col 22} 52.75843{col 34} .2727763{col 46} 37.03233{col 58} 52.22377{col 70}  53.2931
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-5.851884{col 34} .5452218{col 58} -6.92057{col 70}-4.783199
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res}-10.7330
{txt}Ho: diff = 0                                     degrees of freedom = {res}   18429

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12}  9,864{col 22} 7.165876{col 34} .1975028{col 46} 19.61551{col 58}  6.77873{col 70} 7.553021
  {txt}Malawi {c |}{res}{col 12}  8,567{col 22} 13.00341{col 34} .2206403{col 46} 20.42204{col 58}  12.5709{col 70} 13.43592
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 18,431{col 22} 9.879247{col 34} .1488264{col 46} 20.20479{col 58} 9.587534{col 70} 10.17096
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-5.837534{col 34}  .295286{col 58}-6.416322{col 70}-5.258746
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res}-19.7691
{txt}Ho: diff = 0                                     degrees of freedom = {res}   18429

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000
{txt}
{com}. 
. matrix rownames Y = hdd9 sd hdd9_own sd hdd9_purchase sd hdd9_gift sd own_value_share sd purchase_value_share sd other_value_share sd
{txt}
{com}. 
. matrix colnames Y =  % sd
{txt}
{com}. 
. matrix list Y
{res}
{txt}Y[100,5]
                      %         sd         sd         sd         sd
        hdd9 {res}  4.424691  6.2411874          .          .          .
{txt}          sd {res} 1.5593638  1.7475769          .          .          .
{txt}    hdd9_own {res} 1.3885477  1.7033315          .          .          .
{txt}          sd {res} 1.3189334  1.5754372          .          .          .
{txt}hdd9_purch~e {res} 3.0754039  4.9956308          .          .          .
{txt}          sd {res} 1.9660179  2.3106423          .          .          .
{txt}   hdd9_gift {res} .26712652   1.216166          .          .          .
{txt}          sd {res} .64025437  1.2509646          .          .          .
{txt}own_value_~e {res} 42.795733  31.106314          .          .          .
{txt}          sd {res}  39.49981  31.386064          .          .          .
{txt}purchase_v~e {res} 50.038392  55.890276          .          .          .
{txt}          sd {res}  39.60164  33.563594          .          .          .
{txt}other_valu~e {res} 7.1658756  13.003409          .          .          .
{txt}          sd {res} 19.615515  20.422041          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
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{reset}
{com}. frmttable using Table_1_Ethiopia_Malawi.doc, replace  statmat(Y) ctitle("", "Ethiopia", "Malawi") sdec(2)
{res}
{txt}{center:{hline 48}}
{center:{txt}{lalign 22:}{txt}{center 10:Ethiopia}{txt}{center 8:Malawi}{txt}{center 2:}{txt}{center 2:}{txt}{center 2:}}
{txt}{center:{hline 48}}
{center:{txt}{lalign 22:hdd9}{res}{center 10:4.42}{res}{center 8:6.24}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:1.56}{res}{center 8:1.75}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_own}{res}{center 10:1.39}{res}{center 8:1.70}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:1.32}{res}{center 8:1.58}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_purchase}{res}{center 10:3.08}{res}{center 8:5.00}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:1.97}{res}{center 8:2.31}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_gift}{res}{center 10:0.27}{res}{center 8:1.22}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:0.64}{res}{center 8:1.25}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:own_value_share}{res}{center 10:42.80}{res}{center 8:31.11}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:39.50}{res}{center 8:31.39}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:purchase_value_share}{res}{center 10:50.04}{res}{center 8:55.89}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:39.60}{res}{center 8:33.56}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:other_value_share}{res}{center 10:7.17}{res}{center 8:13.00}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:19.62}{res}{center 8:20.42}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{txt}{center:{hline 48}}


{com}. restore
{txt}
{com}. 
. 
. 
. 
. preserve
{txt}
{com}. keep if country==1|country==2
{txt}(64,104 observations deleted)

{com}. mat Y = J(100,5,.)
{txt}
{com}. local tt "  hdd9 hdd9_own hdd9_purchase hdd9_gift  own_value_share purchase_value_share other_value_share"
{txt}
{com}. foreach x of varlist    own_value_share purchase_value_share other_value_share other_crop{c -(}
{txt}  2{com}. replace `x'=`x'*100
{txt}  3{com}. {c )-}
{txt}(12,756 real changes made)
(23,129 real changes made)
(9,758 real changes made)
(888 real changes made)

{com}. 
. 
. local g 1
{txt}
{com}. foreach var of varlist `tt'  {c -(}
{txt}  2{com}. ttest `var', by(country)
{txt}  3{com}. mat Y[`g',1] = r(mu_1)
{txt}  4{com}. mat Y[`g',2] = r(mu_2)
{txt}  5{com}. local g=`g'+1
{txt}  6{com}. mat Y[`g',1] = r(sd_1)
{txt}  7{com}. mat Y[`g',2] = r(sd_2)
{txt}  8{com}. local g=`g'+1
{txt}  9{com}. 
. {c )-}

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  7,046{col 22} 5.704087{col 34} .0199093{col 46} 1.671199{col 58} 5.665059{col 70} 5.743116
 {txt}Nigeria {c |}{res}{col 12} 18,592{col 22} 5.978593{col 34} .0127108{col 46} 1.733145{col 58} 5.953679{col 70} 6.003507
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 25,638{col 22} 5.903152{col 34} .0107463{col 46}  1.72068{col 58} 5.882088{col 70} 5.924215
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.2745055{col 34} .0240111{col 58}-.3215686{col 70}-.2274424
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res}-11.4324
{txt}Ho: diff = 0                                     degrees of freedom = {res}   25636

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  7,044{col 22} .8412834{col 34} .0126402{col 46} 1.060873{col 58} .8165048{col 70} .8660619
 {txt}Nigeria {c |}{res}{col 12} 18,429{col 22} 1.226382{col 34} .0092522{col 46} 1.256015{col 58} 1.208247{col 70} 1.244517
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 25,473{col 22} 1.119892{col 34}  .007628{col 46} 1.217444{col 58}  1.10494{col 70} 1.134843
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} -.385099{col 34} .0168829{col 58}-.4181903{col 70}-.3520076
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res}-22.8100
{txt}Ho: diff = 0                                     degrees of freedom = {res}   25471

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  7,044{col 22} 5.274986{col 34} .0228347{col 46} 1.916486{col 58} 5.230223{col 70} 5.319749
 {txt}Nigeria {c |}{res}{col 12} 18,429{col 22} 5.241359{col 34} .0147576{col 46} 2.003395{col 58} 5.212432{col 70} 5.270285
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 25,473{col 22} 5.250658{col 34} .0124043{col 46} 1.979763{col 58} 5.226344{col 70} 5.274971
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0336271{col 34} .0277325{col 58}-.0207302{col 70} .0879843
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res}  1.2126
{txt}Ho: diff = 0                                     degrees of freedom = {res}   25471

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.8873         {txt}Pr(|T| > |t|) = {res}0.2253          {txt}Pr(T > t) = {res}0.1127

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  7,044{col 22} .4910562{col 34} .0108854{col 46} .9135915{col 58} .4697177{col 70} .5123948
 {txt}Nigeria {c |}{res}{col 12} 18,429{col 22}  .553584{col 34} .0074356{col 46} 1.009407{col 58} .5390096{col 70} .5681585
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 25,473{col 22} .5362933{col 34} .0061667{col 46}  .984225{col 58} .5242062{col 70} .5483805
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0625278{col 34} .0137818{col 58} -.089541{col 70}-.0355146
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res} -4.5370
{txt}Ho: diff = 0                                     degrees of freedom = {res}   25471

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  7,042{col 22} 19.47839{col 34} .3258361{col 46} 27.34307{col 58} 18.83965{col 70} 20.11713
 {txt}Nigeria {c |}{res}{col 12} 16,297{col 22} 23.90709{col 34} .2227987{col 46} 28.44242{col 58} 23.47038{col 70}  24.3438
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 23,339{col 22} 22.57084{col 34} .1845117{col 46} 28.18806{col 58} 22.20918{col 70} 22.93249
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-4.428705{col 34} .4009419{col 58}-5.214577{col 70}-3.642832
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res}-11.0458
{txt}Ho: diff = 0                                     degrees of freedom = {res}   23337

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  7,042{col 22} 75.21914{col 34}  .354189{col 46} 29.72234{col 58} 74.52482{col 70} 75.91345
 {txt}Nigeria {c |}{res}{col 12} 16,297{col 22} 69.79205{col 34} .2347272{col 46} 29.96521{col 58} 69.33196{col 70} 70.25214
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 23,339{col 22} 71.42955{col 34} .1963404{col 46} 29.99513{col 58} 71.04471{col 70} 71.81439
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 5.427084{col 34} .4262813{col 58} 4.591545{col 70} 6.262624
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res} 12.7312
{txt}Ho: diff = 0                                     degrees of freedom = {res}   23337

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  7,042{col 22} 5.302474{col 34} .1712525{col 46} 14.37093{col 58} 4.966768{col 70}  5.63818
 {txt}Nigeria {c |}{res}{col 12} 16,297{col 22} 6.300853{col 34} .1157096{col 46} 14.77146{col 58}  6.07405{col 70} 6.527657
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 23,339{col 22} 5.999616{col 34} .0959515{col 46} 14.65862{col 58} 5.811544{col 70} 6.187687
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.9983796{col 34} .2089437{col 58}-1.407923{col 70}-.5888362
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res} -4.7782
{txt}Ho: diff = 0                                     degrees of freedom = {res}   23337

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000
{txt}
{com}. 
. matrix rownames Y = hdd9 sd hdd9_own sd hdd9_purchase sd hdd9_gift sd own_value_share sd purchase_value_share sd other_value_share sd
{txt}
{com}. 
. matrix colnames Y =  % sd
{txt}
{com}. 
. matrix list Y
{res}
{txt}Y[100,5]
                      %         sd         sd         sd         sd
        hdd9 {res} 5.7040874  5.9785929          .          .          .
{txt}          sd {res}  1.671199  1.7331449          .          .          .
{txt}    hdd9_own {res} .84128336  1.2263823          .          .          .
{txt}          sd {res}  1.060873  1.2560151          .          .          .
{txt}hdd9_purch~e {res} 5.2749858  5.2413587          .          .          .
{txt}          sd {res} 1.9164855  2.0033946          .          .          .
{txt}   hdd9_gift {res} .49105622  .55358403          .          .          .
{txt}          sd {res} .91359155   1.009407          .          .          .
{txt}own_value_~e {res}  19.47839  23.907095          .          .          .
{txt}          sd {res} 27.343068  28.442417          .          .          .
{txt}purchase_v~e {res} 75.219136  69.792052          .          .          .
{txt}          sd {res} 29.722342  29.965211          .          .          .
{txt}other_valu~e {res} 5.3024739  6.3008535          .          .          .
{txt}          sd {res}  14.37093  14.771456          .          .          .
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{reset}
{com}. frmttable using Table_1_Niger_Nigeria.doc, replace  statmat(Y) ctitle("", "Niger", "Nigeria") sdec(2)
{res}
{txt}{center:{hline 46}}
{center:{txt}{lalign 22:}{txt}{center 7:Niger}{txt}{center 9:Nigeria}{txt}{center 2:}{txt}{center 2:}{txt}{center 2:}}
{txt}{center:{hline 46}}
{center:{txt}{lalign 22:hdd9}{res}{center 7:5.70}{res}{center 9:5.98}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:1.67}{res}{center 9:1.73}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_own}{res}{center 7:0.84}{res}{center 9:1.23}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:1.06}{res}{center 9:1.26}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_purchase}{res}{center 7:5.27}{res}{center 9:5.24}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:1.92}{res}{center 9:2.00}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_gift}{res}{center 7:0.49}{res}{center 9:0.55}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:0.91}{res}{center 9:1.01}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:own_value_share}{res}{center 7:19.48}{res}{center 9:23.91}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:27.34}{res}{center 9:28.44}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:purchase_value_share}{res}{center 7:75.22}{res}{center 9:69.79}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:29.72}{res}{center 9:29.97}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:other_value_share}{res}{center 7:5.30}{res}{center 9:6.30}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:14.37}{res}{center 9:14.77}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{txt}{center:{hline 46}}


{com}. restore
{txt}
{com}. 
. 
. 
. preserve
{txt}
{com}. keep if country==4|country==5
{txt}(48,312 observations deleted)

{com}. replace country=0 if country==5     //change the order of country
{txt}(21,117 real changes made)

{com}. 
. mat Y = J(100,5,.)
{txt}
{com}. local tt "  hdd9 hdd9_own hdd9_purchase hdd9_gift  own_value_share purchase_value_share other_value_share"
{txt}
{com}. foreach x of varlist    own_value_share purchase_value_share other_value_share other_crop{c -(}
{txt}  2{com}. replace `x'=`x'*100
{txt}  3{com}. {c )-}
{txt}(25,754 real changes made)
(35,039 real changes made)
(16,393 real changes made)
(10,252 real changes made)

{com}. 
. 
. local g 1
{txt}
{com}. foreach var of varlist `tt'  {c -(}
{txt}  2{com}. ttest `var', by(country)
{txt}  3{com}. mat Y[`g',1] = r(mu_1)
{txt}  4{com}. mat Y[`g',2] = r(mu_2)
{txt}  5{com}. local g=`g'+1
{txt}  6{com}. mat Y[`g',1] = r(sd_1)
{txt}  7{com}. mat Y[`g',2] = r(sd_2)
{txt}  8{com}. local g=`g'+1
{txt}  9{com}. 
. {c )-}

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 21,117{col 22} 5.913387{col 34} .0112206{col 46} 1.630544{col 58} 5.891394{col 70} 5.935381
  {txt}Uganda {c |}{res}{col 12} 20,313{col 22} 5.665387{col 34} .0116948{col 46} 1.666791{col 58} 5.642464{col 70}  5.68831
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 41,430{col 22} 5.791793{col 34} .0081214{col 46} 1.653051{col 58} 5.775875{col 70} 5.807711
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .2480006{col 34} .0162002{col 58} .2162478{col 70} .2797534
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res} 15.3085
{txt}Ho: diff = 0                                     degrees of freedom = {res}   41428

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 17,046{col 22} 1.691247{col 34} .0132087{col 46} 1.724532{col 58} 1.665357{col 70} 1.717138
  {txt}Uganda {c |}{res}{col 12} 20,293{col 22} 2.479131{col 34} .0125542{col 46} 1.788386{col 58} 2.454524{col 70} 2.503738
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 37,339{col 22} 2.119446{col 34} .0093293{col 46} 1.802737{col 58}  2.10116{col 70} 2.137732
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.7878835{col 34} .0182807{col 58}-.8237141{col 70}-.7520529
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res}-43.0993
{txt}Ho: diff = 0                                     degrees of freedom = {res}   37337

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 17,046{col 22} 4.619559{col 34} .0172709{col 46} 2.254891{col 58} 4.585706{col 70} 4.653412
  {txt}Uganda {c |}{res}{col 12} 20,293{col 22}  3.98497{col 34} .0148243{col 46} 2.111779{col 58} 3.955913{col 70} 4.014027
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 37,339{col 22} 4.274673{col 34} .0113907{col 46} 2.201065{col 58} 4.252346{col 70} 4.296999
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .6345887{col 34} .0226313{col 58} .5902306{col 70} .6789467
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res} 28.0403
{txt}Ho: diff = 0                                     degrees of freedom = {res}   37337

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 17,046{col 22} .6541711{col 34} .0074574{col 46} .9736432{col 58} .6395538{col 70} .6687884
  {txt}Uganda {c |}{res}{col 12} 20,293{col 22}   .67713{col 34} .0071294{col 46} 1.015612{col 58} .6631558{col 70} .6911043
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 37,339{col 22} .6666488{col 34} .0051581{col 46} .9967242{col 58} .6565387{col 70} .6767589
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} -.022959{col 34}  .010355{col 58} -.043255{col 70}-.0026629
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res} -2.2172
{txt}Ho: diff = 0                                     degrees of freedom = {res}   37337

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0133         {txt}Pr(|T| > |t|) = {res}0.0266          {txt}Pr(T > t) = {res}0.9867

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 15,944{col 22} 31.72368{col 34} .2730425{col 46} 34.47696{col 58} 31.18849{col 70} 32.25887
  {txt}Uganda {c |}{res}{col 12} 20,289{col 22} 42.57513{col 34} .2254644{col 46} 32.11503{col 58}  42.1332{col 70} 43.01706
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 36,233{col 22} 37.80005{col 34} .1765651{col 46} 33.60911{col 58} 37.45398{col 70} 38.14612
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-10.85145{col 34} .3511036{col 58}-11.53962{col 70}-10.16328
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res}-30.9067
{txt}Ho: diff = 0                                     degrees of freedom = {res}   36231

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 15,944{col 22} 59.78381{col 34} .2842258{col 46} 35.88907{col 58}  59.2267{col 70} 60.34093
  {txt}Uganda {c |}{res}{col 12} 20,289{col 22}  50.2521{col 34} .2254538{col 46} 32.11352{col 58} 49.81019{col 70}   50.694
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 36,233{col 22} 54.44644{col 34} .1794366{col 46} 34.15571{col 58} 54.09474{col 70} 54.79814
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 9.531715{col 34} .3580015{col 58} 8.830021{col 70} 10.23341
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res} 26.6248
{txt}Ho: diff = 0                                     degrees of freedom = {res}   36231

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 15,944{col 22} 8.492509{col 34}  .134169{col 46} 16.94146{col 58} 8.229522{col 70} 8.755495
  {txt}Uganda {c |}{res}{col 12} 20,289{col 22} 7.172774{col 34} .1087573{col 46} 15.49134{col 58} 6.959601{col 70} 7.385947
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 36,233{col 22} 7.753511{col 34} .0848888{col 46} 16.15856{col 58} 7.587127{col 70} 7.919896
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 1.319735{col 34} .1708735{col 58} .9848177{col 70} 1.654652
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res}  7.7235
{txt}Ho: diff = 0                                     degrees of freedom = {res}   36231

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000
{txt}
{com}. 
. matrix rownames Y = hdd9 sd hdd9_own sd hdd9_purchase sd hdd9_gift sd own_value_share sd purchase_value_share sd other_value_share sd
{txt}
{com}. 
. matrix colnames Y =  % sd
{txt}
{com}. 
. matrix list Y
{res}
{txt}Y[100,5]
                      %         sd         sd         sd         sd
        hdd9 {res} 5.9133873  5.6653867          .          .          .
{txt}          sd {res} 1.6305444  1.6667909          .          .          .
{txt}    hdd9_own {res} 1.6912472  2.4791307          .          .          .
{txt}          sd {res} 1.7245324  1.7883862          .          .          .
{txt}hdd9_purch~e {res} 4.6195588  3.9849702          .          .          .
{txt}          sd {res} 2.2548906   2.111779          .          .          .
{txt}   hdd9_gift {res} .65417107  .67713004          .          .          .
{txt}          sd {res} .97364323  1.0156123          .          .          .
{txt}own_value_~e {res}  31.72368  42.575129          .          .          .
{txt}          sd {res} 34.476958  32.115029          .          .          .
{txt}purchase_v~e {res} 59.783812  50.252097          .          .          .
{txt}          sd {res} 35.889066  32.113521          .          .          .
{txt}other_valu~e {res} 8.4925088  7.1727741          .          .          .
{txt}          sd {res} 16.941457  15.491335          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
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{reset}
{com}. frmttable using Table_1_Tanzania_Uganda.doc, replace  statmat(Y) ctitle("", "Tanzania", "Uganda") sdec(2)
{res}
{txt}{center:{hline 48}}
{center:{txt}{lalign 22:}{txt}{center 10:Tanzania}{txt}{center 8:Uganda}{txt}{center 2:}{txt}{center 2:}{txt}{center 2:}}
{txt}{center:{hline 48}}
{center:{txt}{lalign 22:hdd9}{res}{center 10:5.91}{res}{center 8:5.67}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:1.63}{res}{center 8:1.67}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_own}{res}{center 10:1.69}{res}{center 8:2.48}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:1.72}{res}{center 8:1.79}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_purchase}{res}{center 10:4.62}{res}{center 8:3.98}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:2.25}{res}{center 8:2.11}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:hdd9_gift}{res}{center 10:0.65}{res}{center 8:0.68}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:0.97}{res}{center 8:1.02}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:own_value_share}{res}{center 10:31.72}{res}{center 8:42.58}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:34.48}{res}{center 8:32.12}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:purchase_value_share}{res}{center 10:59.78}{res}{center 8:50.25}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:35.89}{res}{center 8:32.11}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:other_value_share}{res}{center 10:8.49}{res}{center 8:7.17}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:16.94}{res}{center 8:15.49}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 22:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{txt}{center:{hline 48}}


{com}. restore
{txt}
{com}. ********************************************************************************
. *                               Table 1                                        *
. ********************************************************************************
. 
. 
. 
. preserve
{txt}
{com}. drop if non_farmer==1
{txt}(22,521 observations deleted)

{com}. 
. mat Y = J(100,5,.)
{txt}
{com}. local tt "   no_species pdd9 pdd_livestock pdd_crop other_crop"
{txt}
{com}. foreach x of varlist     other_crop{c -(}
{txt}  2{com}. replace `x'=`x'*100
{txt}  3{com}. {c )-}
{txt}(17,232 real changes made)

{com}. 
. local g 1
{txt}
{com}. foreach var of varlist `tt'  {c -(}
{txt}  2{com}. ttest `var'=0
{txt}  3{com}. mat Y[`g',1] = r(mu_1)
{txt}  4{com}. local g=`g'+1
{txt}  5{com}. mat Y[`g',1] = r(sd_1)
{txt}  6{com}. local g=`g'+1
{txt}  7{com}. 
. {c )-}

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
no_spe~s {c |}{res}{col 12} 67,221{col 22} 5.545172{col 34} .0128354{col 46} 3.327847{col 58} 5.520014{col 70} 5.570329
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}no_species{txt})                                       t = {res}432.0204
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   67220

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
    pdd9 {c |}{res}{col 12} 67,221{col 22} 3.292528{col 34}  .005826{col 46} 1.510499{col 58} 3.281109{col 70} 3.303947
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}pdd9{txt})                                             t = {res}565.1469
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   67220

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
pdd_li~k {c |}{res}{col 12} 67,221{col 22} 1.068535{col 34} .0033857{col 46} .8778173{col 58} 1.061899{col 70} 1.075171
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}pdd_livestock{txt})                                    t = {res}315.6001
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   67220

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
pdd_crop {c |}{res}{col 12} 67,221{col 22} 2.223993{col 34} .0044124{col 46} 1.144007{col 58} 2.215344{col 70} 2.232641
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}pdd_crop{txt})                                         t = {res}504.0308
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   67220

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
other_~p {c |}{res}{col 12} 67,221{col 22} 25.63485{col 34} .1684034{col 46} 43.66197{col 58} 25.30478{col 70} 25.96492
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}other_crop{txt})                                       t = {res}152.2229
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   67220

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000
{txt}
{com}. 
. matrix rownames Y =  no_species sd pdd9 sd pdd_livestock sd pdd_crop sd other_crop sd
{txt}
{com}. 
. matrix colnames Y =  % sd
{txt}
{com}. 
. matrix list Y
{res}
{txt}Y[100,5]
                      %         sd         sd         sd         sd
  no_species {res} 5.5451719          .          .          .          .
{txt}          sd {res} 3.3278465          .          .          .          .
{txt}        pdd9 {res} 3.2925276          .          .          .          .
{txt}          sd {res} 1.5104995          .          .          .          .
{txt}pdd_livest~k {res} 1.0685351          .          .          .          .
{txt}          sd {res}  .8778173          .          .          .          .
{txt}    pdd_crop {res} 2.2239925          .          .          .          .
{txt}          sd {res} 1.1440072          .          .          .          .
{txt}  other_crop {res} 25.634846          .          .          .          .
{txt}          sd {res}  43.66197          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
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{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
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{txt}          sd {res}         .          .          .          .          .
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{txt}          sd {res}         .          .          .          .          .
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{reset}
{com}. frmttable using Table_1_Whole_Farmer_sample.doc, replace  statmat(Y) ctitle("", "mean", "sd") sdec(2)
{res}
{txt}{center:{hline 34}}
{center:{txt}{lalign 15:}{txt}{center 7:mean}{txt}{center 4:sd}{txt}{center 2:}{txt}{center 2:}{txt}{center 2:}}
{txt}{center:{hline 34}}
{center:{txt}{lalign 15:no_species}{res}{center 7:5.55}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:3.33}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:pdd9}{res}{center 7:3.29}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:1.51}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:pdd_livestock}{res}{center 7:1.07}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:0.88}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:pdd_crop}{res}{center 7:2.22}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:1.14}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:other_crop}{res}{center 7:25.63}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:43.66}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 4:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{txt}{center:{hline 34}}


{com}. restore
{txt}
{com}. 
. 
. 
. 
. 
. preserve
{txt}
{com}. drop if non_farmer==1
{txt}(22,521 observations deleted)

{com}. 
. keep if country==3|country==6
{txt}(49,881 observations deleted)

{com}. mat Y = J(100,5,.)
{txt}
{com}. local tt "   no_species pdd9 pdd_livestock pdd_crop other_crop"
{txt}
{com}. foreach x of varlist     other_crop{c -(}
{txt}  2{com}. replace `x'=`x'*100
{txt}  3{com}. {c )-}
{txt}(6,092 real changes made)

{com}. 
. 
. local g 1
{txt}
{com}. foreach var of varlist `tt'  {c -(}
{txt}  2{com}. ttest `var', by(country)
{txt}  3{com}. mat Y[`g',1] = r(mu_1)
{txt}  4{com}. mat Y[`g',2] = r(mu_2)
{txt}  5{com}. local g=`g'+1
{txt}  6{com}. mat Y[`g',1] = r(sd_1)
{txt}  7{com}. mat Y[`g',2] = r(sd_2)
{txt}  8{com}. local g=`g'+1
{txt}  9{com}. 
. {c )-}

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12}  9,981{col 22} 7.377117{col 34} .0423878{col 46} 4.234751{col 58} 7.294028{col 70} 7.460205
  {txt}Malawi {c |}{res}{col 12}  7,359{col 22} 4.040766{col 34} .0271399{col 46} 2.328189{col 58} 3.987564{col 70} 4.093968
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 17,340{col 22} 5.961188{col 34} .0297447{col 46} 3.916827{col 58} 5.902885{col 70} 6.019491
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}  3.33635{col 34} .0545894{col 58} 3.229349{col 70} 3.443351
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res} 61.1172
{txt}Ho: diff = 0                                     degrees of freedom = {res}   17338

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12}  9,981{col 22} 3.838493{col 34} .0180907{col 46} 1.807346{col 58} 3.803032{col 70} 3.873954
  {txt}Malawi {c |}{res}{col 12}  7,359{col 22} 3.082756{col 34}  .016496{col 46} 1.415107{col 58} 3.050419{col 70} 3.115093
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 17,340{col 22} 3.517762{col 34}  .012864{col 46} 1.693947{col 58} 3.492548{col 70} 3.542977
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .7557373{col 34} .0253873{col 58} .7059757{col 70}  .805499
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res} 29.7683
{txt}Ho: diff = 0                                     degrees of freedom = {res}   17338

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12}  9,981{col 22} 1.637912{col 34} .0096143{col 46} .9605137{col 58} 1.619066{col 70} 1.656758
  {txt}Malawi {c |}{res}{col 12}  7,359{col 22} .7600217{col 34} .0089756{col 46} .7699682{col 58}  .742427{col 70} .7776165
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 17,340{col 22}  1.26534{col 34} .0074827{col 46} .9853348{col 58} 1.250673{col 70} 1.280007
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .8778903{col 34} .0135929{col 58} .8512468{col 70} .9045338
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res} 64.5844
{txt}Ho: diff = 0                                     degrees of freedom = {res}   17338

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12}  9,981{col 22} 2.200581{col 34} .0141302{col 46} 1.411676{col 58} 2.172883{col 70} 2.228279
  {txt}Malawi {c |}{res}{col 12}  7,359{col 22} 2.322734{col 34} .0127182{col 46} 1.091026{col 58} 2.297803{col 70} 2.347665
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 17,340{col 22} 2.252422{col 34} .0097719{col 46} 1.286784{col 58} 2.233268{col 70} 2.271576
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} -.122153{col 34}   .01975{col 58} -.160865{col 70}-.0834409
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res} -6.1850
{txt}Ho: diff = 0                                     degrees of freedom = {res}   17338

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
Ethiopia {c |}{res}{col 12}  9,981{col 22} 47.32993{col 34} .4997866{col 46} 49.93116{col 58} 46.35024{col 70} 48.30961
  {txt}Malawi {c |}{res}{col 12}  7,359{col 22} 18.58948{col 34} .4535175{col 46} 38.90482{col 58} 17.70046{col 70} 19.47851
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 17,340{col 22} 35.13264{col 34} .3625405{col 46} 47.73985{col 58} 34.42203{col 70} 35.84326
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 28.74044{col 34} .7003098{col 58} 27.36777{col 70} 30.11312
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Ethiopia{txt}) - mean({res}Malawi{txt})                          t = {res} 41.0396
{txt}Ho: diff = 0                                     degrees of freedom = {res}   17338

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000
{txt}
{com}. 
. matrix rownames Y =  no_species sd pdd9 sd pdd_livestock sd pdd_crop sd other_crop sd
{txt}
{com}. 
. matrix colnames Y =  % sd
{txt}
{com}. 
. matrix list Y
{res}
{txt}Y[100,5]
                      %         sd         sd         sd         sd
  no_species {res} 7.3771165  4.0407664          .          .          .
{txt}          sd {res} 4.2347514  2.3281889          .          .          .
{txt}        pdd9 {res} 3.8384931  3.0827558          .          .          .
{txt}          sd {res} 1.8073456  1.4151071          .          .          .
{txt}pdd_livest~k {res}  1.637912  .76002174          .          .          .
{txt}          sd {res} .96051371  .76996825          .          .          .
{txt}    pdd_crop {res} 2.2005811  2.3227341          .          .          .
{txt}          sd {res} 1.4116761  1.0910261          .          .          .
{txt}  other_crop {res} 47.329927  18.589482          .          .          .
{txt}          sd {res} 49.931158   38.90482          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
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{reset}
{com}. frmttable using Table_1_Ethiopia_Malawi_Farmer_sample.doc, replace  statmat(Y) ctitle("", "Ethiopia", "Malawi") sdec(2)
{res}
{txt}{center:{hline 41}}
{center:{txt}{lalign 15:}{txt}{center 10:Ethiopia}{txt}{center 8:Malawi}{txt}{center 2:}{txt}{center 2:}{txt}{center 2:}}
{txt}{center:{hline 41}}
{center:{txt}{lalign 15:no_species}{res}{center 10:7.38}{res}{center 8:4.04}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:4.23}{res}{center 8:2.33}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:pdd9}{res}{center 10:3.84}{res}{center 8:3.08}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:1.81}{res}{center 8:1.42}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:pdd_livestock}{res}{center 10:1.64}{res}{center 8:0.76}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:0.96}{res}{center 8:0.77}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:pdd_crop}{res}{center 10:2.20}{res}{center 8:2.32}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:1.41}{res}{center 8:1.09}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:other_crop}{res}{center 10:47.33}{res}{center 8:18.59}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:49.93}{res}{center 8:38.90}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 10:}{res}{center 8:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{txt}{center:{hline 41}}


{com}. restore
{txt}
{com}. 
. 
. 
. 
. preserve
{txt}
{com}. drop if non_farmer==1
{txt}(22,521 observations deleted)

{com}. 
. keep if country==1|country==2
{txt}(49,027 observations deleted)

{com}. mat Y = J(100,5,.)
{txt}
{com}. local tt "   no_species pdd9 pdd_livestock pdd_crop other_crop"
{txt}
{com}. foreach x of varlist     other_crop{c -(}
{txt}  2{com}. replace `x'=`x'*100
{txt}  3{com}. {c )-}
{txt}(888 real changes made)

{com}. 
. 
. local g 1
{txt}
{com}. foreach var of varlist `tt'  {c -(}
{txt}  2{com}. ttest `var', by(country)
{txt}  3{com}. mat Y[`g',1] = r(mu_1)
{txt}  4{com}. mat Y[`g',2] = r(mu_2)
{txt}  5{com}. local g=`g'+1
{txt}  6{com}. mat Y[`g',1] = r(sd_1)
{txt}  7{com}. mat Y[`g',2] = r(sd_2)
{txt}  8{com}. local g=`g'+1
{txt}  9{com}. 
. {c )-}

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  5,312{col 22} 4.450866{col 34} .0325285{col 46} 2.370787{col 58} 4.387097{col 70} 4.514635
 {txt}Nigeria {c |}{res}{col 12} 12,882{col 22} 4.331936{col 34} .0200366{col 46} 2.274137{col 58} 4.292661{col 70} 4.371211
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 18,194{col 22} 4.366659{col 34} .0170763{col 46} 2.303344{col 58} 4.333188{col 70} 4.400131
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .1189299{col 34} .0375487{col 58}  .045331{col 70} .1925288
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res}  3.1674
{txt}Ho: diff = 0                                     degrees of freedom = {res}   18192

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9992         {txt}Pr(|T| > |t|) = {res}0.0015          {txt}Pr(T > t) = {res}0.0008

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  5,312{col 22} 2.481363{col 34} .0149342{col 46} 1.088458{col 58} 2.452086{col 70}  2.51064
 {txt}Nigeria {c |}{res}{col 12} 12,882{col 22} 2.594706{col 34} .0098896{col 46} 1.122459{col 58} 2.575321{col 70} 2.614091
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 18,194{col 22} 2.561614{col 34} .0082574{col 46} 1.113802{col 58} 2.545428{col 70} 2.577799
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.1133428{col 34} .0181425{col 58}-.1489039{col 70}-.0777817
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res} -6.2474
{txt}Ho: diff = 0                                     degrees of freedom = {res}   18192

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  5,312{col 22}  .983622{col 34} .0087654{col 46}   .63885{col 58} .9664383{col 70} 1.000806
 {txt}Nigeria {c |}{res}{col 12} 12,882{col 22}  .744993{col 34} .0052979{col 46} .6013017{col 58} .7346084{col 70} .7553776
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 18,194{col 22} .8146642{col 34} .0046115{col 46} .6220206{col 58} .8056252{col 70} .8237031
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}  .238629{col 34} .0099874{col 58} .2190528{col 70} .2582051
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res} 23.8931
{txt}Ho: diff = 0                                     degrees of freedom = {res}   18192

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  5,312{col 22} 1.497741{col 34}  .013545{col 46} .9872061{col 58} 1.471187{col 70} 1.524295
 {txt}Nigeria {c |}{res}{col 12} 12,882{col 22} 1.849713{col 34} .0082716{col 46} .9388179{col 58} 1.833499{col 70} 1.865926
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 18,194{col 22}  1.74695{col 34} .0071655{col 46} .9665134{col 58} 1.732905{col 70} 1.760995
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.3519718{col 34} .0155427{col 58} -.382437{col 70}-.3215066
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res}-22.6455
{txt}Ho: diff = 0                                     degrees of freedom = {res}   18192

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   Niger {c |}{res}{col 12}  5,312{col 22} 1.054217{col 34} .1401443{col 46}  10.2142{col 58} .7794765{col 70} 1.328957
 {txt}Nigeria {c |}{res}{col 12} 12,882{col 22} 6.458624{col 34} .2165694{col 46} 24.58039{col 58} 6.034116{col 70} 6.883133
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 18,194{col 22}  4.88073{col 34}  .159744{col 46} 21.54709{col 58} 4.567617{col 70} 5.193843
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-5.404408{col 34}  .349061{col 58}  -6.0886{col 70}-4.720215
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Niger{txt}) - mean({res}Nigeria{txt})                            t = {res}-15.4827
{txt}Ho: diff = 0                                     degrees of freedom = {res}   18192

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000
{txt}
{com}. 
. matrix rownames Y =  no_species sd pdd9 sd pdd_livestock sd pdd_crop sd other_crop sd
{txt}
{com}. 
. matrix colnames Y =  % sd
{txt}
{com}. 
. matrix list Y
{res}
{txt}Y[100,5]
                      %         sd         sd         sd         sd
  no_species {res}  4.450866   4.331936          .          .          .
{txt}          sd {res} 2.3707872  2.2741368          .          .          .
{txt}        pdd9 {res}  2.481363  2.5947058          .          .          .
{txt}          sd {res} 1.0884577  1.1224591          .          .          .
{txt}pdd_livest~k {res} .98362199  .74499301          .          .          .
{txt}          sd {res} .63885004  .60130167          .          .          .
{txt}    pdd_crop {res}  1.497741  1.8497128          .          .          .
{txt}          sd {res} .98720614  .93881792          .          .          .
{txt}  other_crop {res} 1.0542169  6.4586244          .          .          .
{txt}          sd {res} 10.214204  24.580389          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
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{reset}
{com}. frmttable using Table_1_Niger_Nigeria_Farmer_sample.doc, replace  statmat(Y) ctitle("", "Niger", "Nigeria") sdec(2)
{res}
{txt}{center:{hline 39}}
{center:{txt}{lalign 15:}{txt}{center 7:Niger}{txt}{center 9:Nigeria}{txt}{center 2:}{txt}{center 2:}{txt}{center 2:}}
{txt}{center:{hline 39}}
{center:{txt}{lalign 15:no_species}{res}{center 7:4.45}{res}{center 9:4.33}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:sd}{res}{center 7:2.37}{res}{center 9:2.27}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 15:sd}{res}{center 7:1.09}{res}{center 9:1.12}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 15:sd}{res}{center 7:0.64}{res}{center 9:0.60}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 15:sd}{res}{center 7:}{res}{center 9:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{txt}{center:{hline 39}}


{com}. restore
{txt}
{com}. 
. 
. 
. preserve
{txt}
{com}. drop if non_farmer==1
{txt}(22,521 observations deleted)

{com}. 
. keep if country==4|country==5
{txt}(35,534 observations deleted)

{com}. replace country=0 if country==5     //change the order of country
{txt}(14,921 real changes made)

{com}. 
. mat Y = J(100,5,.)
{txt}
{com}. local tt "   no_species pdd9 pdd_livestock pdd_crop other_crop"
{txt}
{com}. foreach x of varlist     other_crop{c -(}
{txt}  2{com}. replace `x'=`x'*100
{txt}  3{com}. {c )-}
{txt}(10,252 real changes made)

{com}. 
. 
. local g 1
{txt}
{com}. foreach var of varlist `tt'  {c -(}
{txt}  2{com}. ttest `var', by(country)
{txt}  3{com}. mat Y[`g',1] = r(mu_1)
{txt}  4{com}. mat Y[`g',2] = r(mu_2)
{txt}  5{com}. local g=`g'+1
{txt}  6{com}. mat Y[`g',1] = r(sd_1)
{txt}  7{com}. mat Y[`g',2] = r(sd_2)
{txt}  8{com}. local g=`g'+1
{txt}  9{com}. 
. {c )-}

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 14,921{col 22} 5.852758{col 34} .0311982{col 46} 3.810908{col 58} 5.791606{col 70}  5.91391
  {txt}Uganda {c |}{res}{col 12} 16,766{col 22} 6.120064{col 34} .0215056{col 46} 2.784617{col 58} 6.077911{col 70} 6.162218
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 31,687{col 22} 5.994193{col 34}  .018597{col 46} 3.310429{col 58} 5.957742{col 70} 6.030644
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.2673066{col 34} .0372276{col 58}-.3402741{col 70} -.194339
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res} -7.1803
{txt}Ho: diff = 0                                     degrees of freedom = {res}   31685

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 14,921{col 22} 3.551304{col 34}  .013455{col 46} 1.643555{col 58}  3.52493{col 70} 3.577677
  {txt}Uganda {c |}{res}{col 12} 16,766{col 22}  3.62245{col 34} .0098588{col 46} 1.276555{col 58} 3.603126{col 70} 3.641775
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 31,687{col 22} 3.588948{col 34} .0082092{col 46} 1.461309{col 58} 3.572858{col 70} 3.605039
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0711467{col 34} .0164417{col 58}-.1033731{col 70}-.0389202
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res} -4.3272
{txt}Ho: diff = 0                                     degrees of freedom = {res}   31685

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 14,921{col 22} 1.175457{col 34} .0082021{col 46} 1.001897{col 58}  1.15938{col 70} 1.191534
  {txt}Uganda {c |}{res}{col 12} 16,766{col 22}  1.04533{col 34}  .006234{col 46} .8071981{col 58} 1.033111{col 70} 1.057549
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 31,687{col 22} 1.106605{col 34} .0050921{col 46} .9064332{col 58} 1.096625{col 70} 1.116586
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .1301276{col 34} .0101754{col 58} .1101834{col 70} .1500718
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res} 12.7884
{txt}Ho: diff = 0                                     degrees of freedom = {res}   31685

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 14,921{col 22} 2.375846{col 34} .0098766{col 46} 1.206446{col 58} 2.356487{col 70} 2.395206
  {txt}Uganda {c |}{res}{col 12} 16,766{col 22}  2.57712{col 34} .0070483{col 46} .9126406{col 58} 2.563305{col 70} 2.590936
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 31,687{col 22} 2.482343{col 34} .0059879{col 46} 1.065901{col 58} 2.470606{col 70} 2.494079
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.2012742{col 34}  .011943{col 58}-.2246829{col 70}-.1778655
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res}-16.8529
{txt}Ho: diff = 0                                     degrees of freedom = {res}   31685

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12} 14,921{col 22} 30.19235{col 34} .3758509{col 46} 45.91076{col 58} 29.45563{col 70} 30.92906
  {txt}Uganda {c |}{res}{col 12} 16,766{col 22}  34.2777{col 34}  .366573{col 46} 47.46519{col 58} 33.55918{col 70} 34.99623
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12} 31,687{col 22} 32.35396{col 34} .2628156{col 46}  46.7834{col 58} 31.83883{col 70} 32.86909
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-4.085359{col 34} .5260324{col 58}-5.116403{col 70}-3.054315
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}Uganda{txt})                                 t = {res} -7.7664
{txt}Ho: diff = 0                                     degrees of freedom = {res}   31685

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000
{txt}
{com}. 
. matrix rownames Y =  no_species sd pdd9 sd pdd_livestock sd pdd_crop sd other_crop sd
{txt}
{com}. 
. matrix colnames Y =  % sd
{txt}
{com}. 
. matrix list Y
{res}
{txt}Y[100,5]
                      %         sd         sd         sd         sd
  no_species {res} 5.8527579  6.1200644          .          .          .
{txt}          sd {res} 3.8109085  2.7846166          .          .          .
{txt}        pdd9 {res} 3.5513035  3.6224502          .          .          .
{txt}          sd {res} 1.6435547  1.2765547          .          .          .
{txt}pdd_livest~k {res} 1.1754574  1.0453298          .          .          .
{txt}          sd {res} 1.0018967  .80719806          .          .          .
{txt}    pdd_crop {res} 2.3758461  2.5771204          .          .          .
{txt}          sd {res} 1.2064465  .91264057          .          .          .
{txt}  other_crop {res} 30.192346  34.277705          .          .          .
{txt}          sd {res} 45.910763  47.465185          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
{txt}          sd {res}         .          .          .          .          .
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{reset}
{com}. frmttable using Table_1_Tanzania_Uganda_Farmer_sample.doc, replace  statmat(Y) ctitle("", "Tanzania", "Uganda") sdec(2)
{res}
{txt}{center:{hline 41}}
{center:{txt}{lalign 15:}{txt}{center 10:Tanzania}{txt}{center 8:Uganda}{txt}{center 2:}{txt}{center 2:}{txt}{center 2:}}
{txt}{center:{hline 41}}
{center:{txt}{lalign 15:no_species}{res}{center 10:5.85}{res}{center 8:6.12}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{center:{txt}{lalign 15:sd}{res}{center 10:1.00}{res}{center 8:0.81}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 15:pdd_crop}{res}{center 10:2.38}{res}{center 8:2.58}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
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{txt}{center:{hline 41}}


{com}. restore
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{com}. 
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. tab year, generate(year_)

       {txt}year {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
       2008 {c |}{res}      3,176        3.54        3.54
{txt}       2009 {c |}{res}      2,837        3.16        6.70
{txt}       2010 {c |}{res}     12,719       14.17       20.87
{txt}       2011 {c |}{res}     10,467       11.66       32.54
{txt}       2012 {c |}{res}      9,429       10.51       43.04
{txt}       2013 {c |}{res}     10,027       11.17       54.22
{txt}       2014 {c |}{res}      7,298        8.13       62.35
{txt}       2015 {c |}{res}     12,323       13.73       76.08
{txt}       2016 {c |}{res}      2,447        2.73       78.81
{txt}       2018 {c |}{res}      7,615        8.49       87.29
{txt}       2019 {c |}{res}     11,404       12.71      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     89,742      100.00
{txt}
{com}. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop hdd9 pdd9 no_species{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. global year_NIGER year_4
{txt}
{com}. global year_NIGERIA year_3 year_5 year_8
{txt}
{com}. global year_ETHIOPIA year_6
{txt}
{com}. global year_UGANDA   year_3 year_4 year_6 year_8 year_10
{txt}
{com}. global year_TANZANIA year_1 year_5 year_7
{txt}
{com}. global year_MALAWI year_3 year_6 
{txt}
{com}. global xlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop  motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean  
{txt}
{com}. 
. 
. 
. 
. ********************************************************************************
. *               Figure 1_Impact of Production Diversity by Countries           *
. ********************************************************************************
. preserve
{txt}
{com}. eststo clear
{txt}
{com}. *whole
. xtreg hdd9  pdd9   $xlist  pdd9_mean i.country i.year  , cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    89,742
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    36,644

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0290                                         {txt}min = {res}         1
{txt}     between = {res}0.3561                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2856                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 27347.26
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:36,644} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .100046{col 30}{space 2} .0051959{col 41}{space 1}   19.25{col 50}{space 3}0.000{col 58}{space 4} .0898622{col 71}{space 3} .1102297
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0030401{col 30}{space 2} .0022275{col 41}{space 1}   -1.36{col 50}{space 3}0.172{col 58}{space 4} -.007406{col 71}{space 3} .0013258
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .065032{col 30}{space 2}   .02411{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .0177772{col 71}{space 3} .1122868
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0004217{col 30}{space 2}   .00041{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.0003818{col 71}{space 3} .0012253
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0496982{col 30}{space 2} .0143935{col 41}{space 1}    3.45{col 50}{space 3}0.001{col 58}{space 4} .0214874{col 71}{space 3}  .077909
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3002783{col 30}{space 2} .0134006{col 41}{space 1}   22.41{col 50}{space 3}0.000{col 58}{space 4} .2740137{col 71}{space 3} .3265429
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1228612{col 30}{space 2} .0252171{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .0734365{col 71}{space 3} .1722858
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2169943{col 30}{space 2} .0173222{col 41}{space 1}   12.53{col 50}{space 3}0.000{col 58}{space 4} .1830434{col 71}{space 3} .2509452
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1804894{col 30}{space 2}  .019958{col 41}{space 1}    9.04{col 50}{space 3}0.000{col 58}{space 4} .1413725{col 71}{space 3} .2196063
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1260233{col 30}{space 2} .0166278{col 41}{space 1}    7.58{col 50}{space 3}0.000{col 58}{space 4} .0934334{col 71}{space 3} .1586132
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2200247{col 30}{space 2} .0155761{col 41}{space 1}   14.13{col 50}{space 3}0.000{col 58}{space 4}  .189496{col 71}{space 3} .2505533
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0865284{col 30}{space 2} .0128051{col 41}{space 1}   -6.76{col 50}{space 3}0.000{col 58}{space 4} -.111626{col 71}{space 3}-.0614309
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003881{col 30}{space 2} .0009502{col 41}{space 1}    0.41{col 50}{space 3}0.683{col 58}{space 4}-.0014743{col 71}{space 3} .0022504
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0966535{col 30}{space 2} .0148938{col 41}{space 1}    6.49{col 50}{space 3}0.000{col 58}{space 4} .0674622{col 71}{space 3} .1258448
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0706861{col 30}{space 2} .0343358{col 41}{space 1}    2.06{col 50}{space 3}0.040{col 58}{space 4} .0033892{col 71}{space 3}  .137983
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5467516{col 30}{space 2} .0254487{col 41}{space 1}   21.48{col 50}{space 3}0.000{col 58}{space 4} .4968731{col 71}{space 3} .5966302
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6966126{col 30}{space 2} .0272048{col 41}{space 1}   25.61{col 50}{space 3}0.000{col 58}{space 4} .6432923{col 71}{space 3}  .749933
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .240854{col 30}{space 2}  .024667{col 41}{space 1}    9.76{col 50}{space 3}0.000{col 58}{space 4} .1925076{col 71}{space 3} .2892004
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1894021{col 30}{space 2} .0221414{col 41}{space 1}    8.55{col 50}{space 3}0.000{col 58}{space 4} .1460057{col 71}{space 3} .2327984
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0503437{col 30}{space 2} .0067234{col 41}{space 1}   -7.49{col 50}{space 3}0.000{col 58}{space 4}-.0635213{col 71}{space 3}-.0371661
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3034848{col 30}{space 2} .0295445{col 41}{space 1}  -10.27{col 50}{space 3}0.000{col 58}{space 4}-.3613909{col 71}{space 3}-.2455787
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.372043{col 30}{space 2}   .02916{col 41}{space 1}  -47.05{col 50}{space 3}0.000{col 58}{space 4}-1.429196{col 71}{space 3}-1.314891
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.3849754{col 30}{space 2} .0291919{col 41}{space 1}  -13.19{col 50}{space 3}0.000{col 58}{space 4}-.4421905{col 71}{space 3}-.3277604
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.1965689{col 30}{space 2} .0278902{col 41}{space 1}   -7.05{col 50}{space 3}0.000{col 58}{space 4}-.2512327{col 71}{space 3}-.1419051
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .6739114{col 30}{space 2} .0337996{col 41}{space 1}   19.94{col 50}{space 3}0.000{col 58}{space 4} .6076653{col 71}{space 3} .7401575
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2256059{col 30}{space 2} .0385288{col 41}{space 1}   -5.86{col 50}{space 3}0.000{col 58}{space 4} -.301121{col 71}{space 3}-.1500909
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0506931{col 30}{space 2} .0276656{col 41}{space 1}   -1.83{col 50}{space 3}0.067{col 58}{space 4}-.1049168{col 71}{space 3} .0035305
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0427377{col 30}{space 2} .0318888{col 41}{space 1}    1.34{col 50}{space 3}0.180{col 58}{space 4}-.0197632{col 71}{space 3} .1052386
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0060608{col 30}{space 2}  .028045{col 41}{space 1}    0.22{col 50}{space 3}0.829{col 58}{space 4}-.0489064{col 71}{space 3}  .061028
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0529548{col 30}{space 2}  .031712{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0091995{col 71}{space 3} .1151091
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0722623{col 30}{space 2} .0318453{col 41}{space 1}   -2.27{col 50}{space 3}0.023{col 58}{space 4} -.134678{col 71}{space 3}-.0098466
{txt}{space 11}2015  {c |}{col 18}{res}{space 2}  .143557{col 30}{space 2} .0306107{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0835611{col 71}{space 3}  .203553
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2290239{col 30}{space 2} .0424158{col 41}{space 1}   -5.40{col 50}{space 3}0.000{col 58}{space 4}-.3121573{col 71}{space 3}-.1458906
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3829816{col 30}{space 2} .0329361{col 41}{space 1}   11.63{col 50}{space 3}0.000{col 58}{space 4} .3184281{col 71}{space 3} .4475352
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0976156{col 30}{space 2} .0300959{col 41}{space 1}   -3.24{col 50}{space 3}0.001{col 58}{space 4}-.1566024{col 71}{space 3}-.0386288
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.464915{col 30}{space 2} .0458253{col 41}{space 1}   97.43{col 50}{space 3}0.000{col 58}{space 4} 4.375099{col 71}{space 3} 4.554731
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .81463678
         {txt}sigma_e {c |} {res} 1.2548029
             {txt}rho {c |} {res} .29650786{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. rename  pdd9       pdd9_1
{res}{txt}
{com}. rename  no_species pdd9
{res}{txt}
{com}. xtreg hdd9  pdd9   $xlist  no_species_mean i.country i.year  , cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    89,742
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    36,644

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0269                                         {txt}min = {res}         1
{txt}     between = {res}0.3549                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2842                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 26961.43
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:36,644} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0443685{col 30}{space 2} .0028497{col 41}{space 1}   15.57{col 50}{space 3}0.000{col 58}{space 4} .0387831{col 71}{space 3} .0499538
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.002285{col 30}{space 2} .0022411{col 41}{space 1}   -1.02{col 50}{space 3}0.308{col 58}{space 4}-.0066775{col 71}{space 3} .0021075
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0719461{col 30}{space 2} .0241382{col 41}{space 1}    2.98{col 50}{space 3}0.003{col 58}{space 4} .0246361{col 71}{space 3} .1192561
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0005157{col 30}{space 2} .0004112{col 41}{space 1}    1.25{col 50}{space 3}0.210{col 58}{space 4}-.0002903{col 71}{space 3} .0013217
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0485595{col 30}{space 2} .0144281{col 41}{space 1}    3.37{col 50}{space 3}0.001{col 58}{space 4}  .020281{col 71}{space 3} .0768381
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3001698{col 30}{space 2}  .013424{col 41}{space 1}   22.36{col 50}{space 3}0.000{col 58}{space 4} .2738592{col 71}{space 3} .3264804
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1242362{col 30}{space 2} .0252541{col 41}{space 1}    4.92{col 50}{space 3}0.000{col 58}{space 4} .0747391{col 71}{space 3} .1737333
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2185919{col 30}{space 2} .0173342{col 41}{space 1}   12.61{col 50}{space 3}0.000{col 58}{space 4} .1846175{col 71}{space 3} .2525663
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1819554{col 30}{space 2} .0199802{col 41}{space 1}    9.11{col 50}{space 3}0.000{col 58}{space 4} .1427949{col 71}{space 3} .2211159
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1249443{col 30}{space 2} .0166514{col 41}{space 1}    7.50{col 50}{space 3}0.000{col 58}{space 4} .0923081{col 71}{space 3} .1575804
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2194709{col 30}{space 2}  .015602{col 41}{space 1}   14.07{col 50}{space 3}0.000{col 58}{space 4} .1888915{col 71}{space 3} .2500502
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0811529{col 30}{space 2} .0128192{col 41}{space 1}   -6.33{col 50}{space 3}0.000{col 58}{space 4}-.1062781{col 71}{space 3}-.0560277
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0005239{col 30}{space 2} .0009503{col 41}{space 1}    0.55{col 50}{space 3}0.581{col 58}{space 4}-.0013386{col 71}{space 3} .0023864
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0646104{col 30}{space 2} .0158448{col 41}{space 1}    4.08{col 50}{space 3}0.000{col 58}{space 4} .0335552{col 71}{space 3} .0956656
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0744849{col 30}{space 2} .0343454{col 41}{space 1}    2.17{col 50}{space 3}0.030{col 58}{space 4} .0071692{col 71}{space 3} .1418006
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5433875{col 30}{space 2} .0254747{col 41}{space 1}   21.33{col 50}{space 3}0.000{col 58}{space 4} .4934581{col 71}{space 3} .5933169
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6815034{col 30}{space 2} .0271937{col 41}{space 1}   25.06{col 50}{space 3}0.000{col 58}{space 4} .6282048{col 71}{space 3} .7348019
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2352794{col 30}{space 2} .0246578{col 41}{space 1}    9.54{col 50}{space 3}0.000{col 58}{space 4}  .186951{col 71}{space 3} .2836078
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1860975{col 30}{space 2} .0221543{col 41}{space 1}    8.40{col 50}{space 3}0.000{col 58}{space 4} .1426758{col 71}{space 3} .2295192
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0213853{col 30}{space 2} .0035172{col 41}{space 1}   -6.08{col 50}{space 3}0.000{col 58}{space 4} -.028279{col 71}{space 3}-.0144917
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.2932313{col 30}{space 2} .0295588{col 41}{space 1}   -9.92{col 50}{space 3}0.000{col 58}{space 4}-.3511656{col 71}{space 3}-.2352971
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.358575{col 30}{space 2} .0292904{col 41}{space 1}  -46.38{col 50}{space 3}0.000{col 58}{space 4}-1.415983{col 71}{space 3}-1.301167
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.3556034{col 30}{space 2} .0289791{col 41}{space 1}  -12.27{col 50}{space 3}0.000{col 58}{space 4}-.4124015{col 71}{space 3}-.2988053
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.1726939{col 30}{space 2} .0277016{col 41}{space 1}   -6.23{col 50}{space 3}0.000{col 58}{space 4} -.226988{col 71}{space 3}-.1183997
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .7107227{col 30}{space 2} .0336557{col 41}{space 1}   21.12{col 50}{space 3}0.000{col 58}{space 4} .6447588{col 71}{space 3} .7766866
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2615948{col 30}{space 2} .0385206{col 41}{space 1}   -6.79{col 50}{space 3}0.000{col 58}{space 4}-.3370938{col 71}{space 3}-.1860959
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0710649{col 30}{space 2} .0276785{col 41}{space 1}   -2.57{col 50}{space 3}0.010{col 58}{space 4}-.1253138{col 71}{space 3}-.0168161
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0286766{col 30}{space 2} .0318984{col 41}{space 1}    0.90{col 50}{space 3}0.369{col 58}{space 4} -.033843{col 71}{space 3} .0911963
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0095074{col 30}{space 2} .0280498{col 41}{space 1}   -0.34{col 50}{space 3}0.735{col 58}{space 4} -.064484{col 71}{space 3} .0454691
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0421374{col 30}{space 2} .0317725{col 41}{space 1}    1.33{col 50}{space 3}0.185{col 58}{space 4}-.0201355{col 71}{space 3} .1044104
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0810557{col 30}{space 2} .0318817{col 41}{space 1}   -2.54{col 50}{space 3}0.011{col 58}{space 4}-.1435427{col 71}{space 3}-.0185688
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1334589{col 30}{space 2} .0306383{col 41}{space 1}    4.36{col 50}{space 3}0.000{col 58}{space 4} .0734089{col 71}{space 3} .1935089
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2460099{col 30}{space 2} .0423465{col 41}{space 1}   -5.81{col 50}{space 3}0.000{col 58}{space 4}-.3290074{col 71}{space 3}-.1630123
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3827753{col 30}{space 2} .0329631{col 41}{space 1}   11.61{col 50}{space 3}0.000{col 58}{space 4} .3181687{col 71}{space 3} .4473818
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.1022424{col 30}{space 2} .0301381{col 41}{space 1}   -3.39{col 50}{space 3}0.001{col 58}{space 4} -.161312{col 71}{space 3}-.0431728
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.485908{col 30}{space 2} .0457436{col 41}{space 1}   98.07{col 50}{space 3}0.000{col 58}{space 4} 4.396252{col 71}{space 3} 4.575564
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .8149875
         {txt}sigma_e {c |} {res} 1.2559737
             {txt}rho {c |} {res} .29629841{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. *Ethiopia
. xtreg hdd9  pdd9_1    $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    13,511
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,436

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0229                                         {txt}min = {res}         1
{txt}     between = {res}0.3713                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2595                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  3554.62
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,436} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_1 {c |}{col 18}{res}{space 2} .0512984{col 30}{space 2} .0105844{col 41}{space 1}    4.85{col 50}{space 3}0.000{col 58}{space 4} .0305533{col 71}{space 3} .0720434
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0476754{col 30}{space 2} .0070238{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4}  .033909{col 71}{space 3} .0614419
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0241072{col 30}{space 2} .0538657{col 41}{space 1}   -0.45{col 50}{space 3}0.654{col 58}{space 4} -.129682{col 71}{space 3} .0814675
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0028044{col 30}{space 2} .0009433{col 41}{space 1}   -2.97{col 50}{space 3}0.003{col 58}{space 4}-.0046533{col 71}{space 3}-.0009555
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0094981{col 30}{space 2} .0330836{col 41}{space 1}   -0.29{col 50}{space 3}0.774{col 58}{space 4}-.0743408{col 71}{space 3} .0553446
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .4064271{col 30}{space 2} .0299839{col 41}{space 1}   13.55{col 50}{space 3}0.000{col 58}{space 4} .3476596{col 71}{space 3} .4651945
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1383359{col 30}{space 2} .1324753{col 41}{space 1}   -1.04{col 50}{space 3}0.296{col 58}{space 4}-.3979828{col 71}{space 3} .1213109
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1920371{col 30}{space 2} .0369299{col 41}{space 1}    5.20{col 50}{space 3}0.000{col 58}{space 4} .1196558{col 71}{space 3} .2644183
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1469872{col 30}{space 2} .0451321{col 41}{space 1}    3.26{col 50}{space 3}0.001{col 58}{space 4} .0585299{col 71}{space 3} .2354444
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0335136{col 30}{space 2} .0535953{col 41}{space 1}   -0.63{col 50}{space 3}0.532{col 58}{space 4}-.1385585{col 71}{space 3} .0715312
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2115585{col 30}{space 2} .0471208{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .1192036{col 71}{space 3} .3039135
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1698553{col 30}{space 2}  .029409{col 41}{space 1}   -5.78{col 50}{space 3}0.000{col 58}{space 4} -.227496{col 71}{space 3}-.1122146
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0061977{col 30}{space 2} .0034661{col 41}{space 1}    1.79{col 50}{space 3}0.074{col 58}{space 4}-.0005957{col 71}{space 3} .0129912
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2097884{col 30}{space 2} .0311529{col 41}{space 1}    6.73{col 50}{space 3}0.000{col 58}{space 4} .1487299{col 71}{space 3} .2708469
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.169987{col 30}{space 2} .2161981{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4} .7462466{col 71}{space 3} 1.593727
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5327733{col 30}{space 2} .0561351{col 41}{space 1}    9.49{col 50}{space 3}0.000{col 58}{space 4} .4227504{col 71}{space 3} .6427961
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6664552{col 30}{space 2} .0671361{col 41}{space 1}    9.93{col 50}{space 3}0.000{col 58}{space 4} .5348708{col 71}{space 3} .7980395
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5003858{col 30}{space 2} .0814643{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4} .3407187{col 71}{space 3} .6600529
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0848497{col 30}{space 2} .0598687{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0324908{col 71}{space 3} .2021902
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0039661{col 30}{space 2} .0142828{col 41}{space 1}    0.28{col 50}{space 3}0.781{col 58}{space 4}-.0240277{col 71}{space 3} .0319599
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1924394{col 30}{space 2} .0211475{col 41}{space 1}   -9.10{col 50}{space 3}0.000{col 58}{space 4}-.2338878{col 71}{space 3} -.150991
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.169398{col 30}{space 2}  .068152{col 41}{space 1}   46.50{col 50}{space 3}0.000{col 58}{space 4} 3.035822{col 71}{space 3} 3.302973
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76124145
         {txt}sigma_e {c |} {res} 1.1126502
             {txt}rho {c |} {res} .31884193{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. rename  pdd9_1       pdd9_2
{res}{txt}
{com}. rename  pdd9       pdd9_1
{res}{txt}
{com}. xtreg hdd9  pdd9_1    $xlist  no_species_mean $year_ETHIOPIA if country==3, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    13,511
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,436

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0214                                         {txt}min = {res}         1
{txt}     between = {res}0.3701                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2576                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  3484.36
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,436} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_1 {c |}{col 18}{res}{space 2} .0166213{col 30}{space 2} .0055063{col 41}{space 1}    3.02{col 50}{space 3}0.003{col 58}{space 4} .0058293{col 71}{space 3} .0274134
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0506938{col 30}{space 2}  .007001{col 41}{space 1}    7.24{col 50}{space 3}0.000{col 58}{space 4} .0369721{col 71}{space 3} .0644154
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0147286{col 30}{space 2} .0539529{col 41}{space 1}   -0.27{col 50}{space 3}0.785{col 58}{space 4}-.1204744{col 71}{space 3} .0910172
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0028529{col 30}{space 2} .0009473{col 41}{space 1}   -3.01{col 50}{space 3}0.003{col 58}{space 4}-.0047096{col 71}{space 3}-.0009962
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0148551{col 30}{space 2} .0331161{col 41}{space 1}   -0.45{col 50}{space 3}0.654{col 58}{space 4}-.0797615{col 71}{space 3} .0500513
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .405636{col 30}{space 2} .0301005{col 41}{space 1}   13.48{col 50}{space 3}0.000{col 58}{space 4} .3466402{col 71}{space 3} .4646319
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1238802{col 30}{space 2} .1319335{col 41}{space 1}   -0.94{col 50}{space 3}0.348{col 58}{space 4}-.3824652{col 71}{space 3} .1347048
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1960387{col 30}{space 2}  .036964{col 41}{space 1}    5.30{col 50}{space 3}0.000{col 58}{space 4} .1235907{col 71}{space 3} .2684868
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1532508{col 30}{space 2} .0451367{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .0647844{col 71}{space 3} .2417171
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0349639{col 30}{space 2}   .05357{col 41}{space 1}   -0.65{col 50}{space 3}0.514{col 58}{space 4}-.1399591{col 71}{space 3} .0700313
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2084507{col 30}{space 2} .0471412{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .1160557{col 71}{space 3} .3008458
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1665288{col 30}{space 2} .0294391{col 41}{space 1}   -5.66{col 50}{space 3}0.000{col 58}{space 4}-.2242283{col 71}{space 3}-.1088293
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .007588{col 30}{space 2}  .003466{col 41}{space 1}    2.19{col 50}{space 3}0.029{col 58}{space 4} .0007947{col 71}{space 3} .0143812
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .222695{col 30}{space 2} .0333524{col 41}{space 1}    6.68{col 50}{space 3}0.000{col 58}{space 4} .1573254{col 71}{space 3} .2880646
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.149641{col 30}{space 2} .2152657{col 41}{space 1}    5.34{col 50}{space 3}0.000{col 58}{space 4} .7277277{col 71}{space 3} 1.571554
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5229237{col 30}{space 2} .0562509{col 41}{space 1}    9.30{col 50}{space 3}0.000{col 58}{space 4} .4126739{col 71}{space 3} .6331734
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6254583{col 30}{space 2} .0668855{col 41}{space 1}    9.35{col 50}{space 3}0.000{col 58}{space 4} .4943651{col 71}{space 3} .7565515
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}   .48054{col 30}{space 2} .0811811{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .3214279{col 71}{space 3} .6396521
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0884969{col 30}{space 2} .0598379{col 41}{space 1}    1.48{col 50}{space 3}0.139{col 58}{space 4}-.0287832{col 71}{space 3} .2057769
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}  .001267{col 30}{space 2} .0068525{col 41}{space 1}    0.18{col 50}{space 3}0.853{col 58}{space 4}-.0121636{col 71}{space 3} .0146977
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1918565{col 30}{space 2} .0216135{col 41}{space 1}   -8.88{col 50}{space 3}0.000{col 58}{space 4}-.2342182{col 71}{space 3}-.1494949
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.225873{col 30}{space 2} .0667081{col 41}{space 1}   48.36{col 50}{space 3}0.000{col 58}{space 4} 3.095127{col 71}{space 3} 3.356618
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7621519
         {txt}sigma_e {c |} {res} 1.1132581
             {txt}rho {c |} {res} .31912394{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. *Malawi
. xtreg hdd9  pdd9_2    $xlist  pdd9_mean $year_MALAWI if country==6, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,163
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,447

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0401                                         {txt}min = {res}         1
{txt}     between = {res}0.3706                                         {txt}avg = {res}       2.7
{txt}     overall = {res}0.2936                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  3127.04
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_2 {c |}{col 18}{res}{space 2} .1160662{col 30}{space 2}  .014321{col 41}{space 1}    8.10{col 50}{space 3}0.000{col 58}{space 4} .0879976{col 71}{space 3} .1441349
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0117709{col 30}{space 2} .0087768{col 41}{space 1}   -1.34{col 50}{space 3}0.180{col 58}{space 4}-.0289731{col 71}{space 3} .0054313
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3383894{col 30}{space 2} .0733556{col 41}{space 1}   -4.61{col 50}{space 3}0.000{col 58}{space 4}-.4821638{col 71}{space 3} -.194615
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0031304{col 30}{space 2} .0012647{col 41}{space 1}   -2.48{col 50}{space 3}0.013{col 58}{space 4}-.0056092{col 71}{space 3}-.0006516
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0999807{col 30}{space 2} .0419376{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4}-.1821768{col 71}{space 3}-.0177845
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2929747{col 30}{space 2} .0447797{col 41}{space 1}    6.54{col 50}{space 3}0.000{col 58}{space 4} .2052081{col 71}{space 3} .3807413
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2489785{col 30}{space 2}  .136827{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4}-.0191975{col 71}{space 3} .5171544
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2573716{col 30}{space 2} .0528726{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .1537432{col 71}{space 3}     .361
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4530508{col 30}{space 2} .0857548{col 41}{space 1}    5.28{col 50}{space 3}0.000{col 58}{space 4} .2849744{col 71}{space 3} .6211272
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1757857{col 30}{space 2}  .056304{col 41}{space 1}    3.12{col 50}{space 3}0.002{col 58}{space 4} .0654319{col 71}{space 3} .2861394
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2602988{col 30}{space 2} .0413476{col 41}{space 1}    6.30{col 50}{space 3}0.000{col 58}{space 4} .1792591{col 71}{space 3} .3413386
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1950077{col 30}{space 2} .0327526{col 41}{space 1}   -5.95{col 50}{space 3}0.000{col 58}{space 4}-.2592016{col 71}{space 3}-.1308138
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0228484{col 30}{space 2} .0262653{col 41}{space 1}    0.87{col 50}{space 3}0.384{col 58}{space 4}-.0286307{col 71}{space 3} .0743275
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0309318{col 30}{space 2} .0473574{col 41}{space 1}    0.65{col 50}{space 3}0.514{col 58}{space 4}-.0618871{col 71}{space 3} .1237506
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3134129{col 30}{space 2}  .212582{col 41}{space 1}    1.47{col 50}{space 3}0.140{col 58}{space 4}-.1032402{col 71}{space 3}  .730066
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4575541{col 30}{space 2} .0763532{col 41}{space 1}    5.99{col 50}{space 3}0.000{col 58}{space 4} .3079046{col 71}{space 3} .6072035
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7258006{col 30}{space 2} .1103959{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .5094286{col 71}{space 3} .9421725
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3856524{col 30}{space 2} .0789567{col 41}{space 1}    4.88{col 50}{space 3}0.000{col 58}{space 4} .2309001{col 71}{space 3} .5404047
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3399225{col 30}{space 2} .0675471{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .2075325{col 71}{space 3} .4723124
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0780017{col 30}{space 2} .0206163{col 41}{space 1}   -3.78{col 50}{space 3}0.000{col 58}{space 4}-.1184089{col 71}{space 3}-.0375944
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}  .116201{col 30}{space 2} .0419337{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4} .0340125{col 71}{space 3} .1983895
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0837529{col 30}{space 2} .0350109{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0151328{col 71}{space 3}  .152373
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.318584{col 30}{space 2} .0879862{col 41}{space 1}   60.45{col 50}{space 3}0.000{col 58}{space 4} 5.146134{col 71}{space 3} 5.491034
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69413719
         {txt}sigma_e {c |} {res} 1.3063515
             {txt}rho {c |} {res} .22017486{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. rename  pdd9_2       pdd9_3
{res}{txt}
{com}. rename  pdd9_1       pdd9_2
{res}{txt}
{com}. 
. xtreg hdd9  pdd9_2    $xlist  no_species_mean $year_MALAWI if country==6, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,163
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,447

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0420                                         {txt}min = {res}         1
{txt}     between = {res}0.3713                                         {txt}avg = {res}       2.7
{txt}     overall = {res}0.2949                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  3141.98
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_2 {c |}{col 18}{res}{space 2} .0899114{col 30}{space 2} .0098858{col 41}{space 1}    9.09{col 50}{space 3}0.000{col 58}{space 4} .0705355{col 71}{space 3} .1092873
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0116703{col 30}{space 2} .0087587{col 41}{space 1}   -1.33{col 50}{space 3}0.183{col 58}{space 4} -.028837{col 71}{space 3} .0054963
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3331084{col 30}{space 2} .0732846{col 41}{space 1}   -4.55{col 50}{space 3}0.000{col 58}{space 4}-.4767436{col 71}{space 3}-.1894732
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0032715{col 30}{space 2} .0012689{col 41}{space 1}   -2.58{col 50}{space 3}0.010{col 58}{space 4}-.0057584{col 71}{space 3}-.0007845
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0998213{col 30}{space 2} .0419066{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4}-.1819567{col 71}{space 3}-.0176858
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2942003{col 30}{space 2} .0447884{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .2064166{col 71}{space 3} .3819841
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .233312{col 30}{space 2} .1365571{col 41}{space 1}    1.71{col 50}{space 3}0.088{col 58}{space 4}-.0343349{col 71}{space 3}  .500959
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2555796{col 30}{space 2} .0526945{col 41}{space 1}    4.85{col 50}{space 3}0.000{col 58}{space 4} .1523002{col 71}{space 3}  .358859
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4475193{col 30}{space 2} .0857579{col 41}{space 1}    5.22{col 50}{space 3}0.000{col 58}{space 4}  .279437{col 71}{space 3} .6156016
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1818363{col 30}{space 2} .0563267{col 41}{space 1}    3.23{col 50}{space 3}0.001{col 58}{space 4}  .071438{col 71}{space 3} .2922347
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2616892{col 30}{space 2} .0413364{col 41}{space 1}    6.33{col 50}{space 3}0.000{col 58}{space 4} .1806713{col 71}{space 3}  .342707
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1917017{col 30}{space 2} .0327404{col 41}{space 1}   -5.86{col 50}{space 3}0.000{col 58}{space 4}-.2558716{col 71}{space 3}-.1275318
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0135831{col 30}{space 2} .0262597{col 41}{space 1}    0.52{col 50}{space 3}0.605{col 58}{space 4}-.0378849{col 71}{space 3} .0650511
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0546488{col 30}{space 2} .0484106{col 41}{space 1}   -1.13{col 50}{space 3}0.259{col 58}{space 4}-.1495318{col 71}{space 3} .0402341
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3249635{col 30}{space 2}  .212399{col 41}{space 1}    1.53{col 50}{space 3}0.126{col 58}{space 4}-.0913308{col 71}{space 3} .7412579
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4628961{col 30}{space 2} .0761613{col 41}{space 1}    6.08{col 50}{space 3}0.000{col 58}{space 4} .3136228{col 71}{space 3} .6121695
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .728563{col 30}{space 2} .1097915{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .5133756{col 71}{space 3} .9437504
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3821026{col 30}{space 2} .0790402{col 41}{space 1}    4.83{col 50}{space 3}0.000{col 58}{space 4} .2271866{col 71}{space 3} .5370185
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3380611{col 30}{space 2} .0675557{col 41}{space 1}    5.00{col 50}{space 3}0.000{col 58}{space 4} .2056543{col 71}{space 3} .4704679
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0564073{col 30}{space 2} .0136416{col 41}{space 1}   -4.13{col 50}{space 3}0.000{col 58}{space 4}-.0831444{col 71}{space 3}-.0296701
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .1199118{col 30}{space 2}  .042024{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0375462{col 71}{space 3} .2022773
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0671032{col 30}{space 2} .0350129{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4}-.0015208{col 71}{space 3} .1357273
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.323738{col 30}{space 2} .0863889{col 41}{space 1}   61.63{col 50}{space 3}0.000{col 58}{space 4} 5.154419{col 71}{space 3} 5.493057
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69442314
         {txt}sigma_e {c |} {res} 1.3052971
             {txt}rho {c |} {res} .22059386{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. *Niger
. xtreg hdd9  pdd9_3    $xlist  pdd9_mean $year_NIGER if country==1, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,046
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,069

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0394                                         {txt}min = {res}         1
{txt}     between = {res}0.2380                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1908                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1600.06
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_3 {c |}{col 18}{res}{space 2} .2448114{col 30}{space 2} .0346647{col 41}{space 1}    7.06{col 50}{space 3}0.000{col 58}{space 4} .1768697{col 71}{space 3}  .312753
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0138424{col 30}{space 2} .0064218{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0012558{col 71}{space 3} .0264289
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0341181{col 30}{space 2} .0962046{col 41}{space 1}   -0.35{col 50}{space 3}0.723{col 58}{space 4}-.2226757{col 71}{space 3} .1544396
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0028576{col 30}{space 2} .0013875{col 41}{space 1}    2.06{col 50}{space 3}0.039{col 58}{space 4} .0001383{col 71}{space 3}  .005577
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1124151{col 30}{space 2} .0575238{col 41}{space 1}    1.95{col 50}{space 3}0.051{col 58}{space 4}-.0003294{col 71}{space 3} .2251595
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3465292{col 30}{space 2} .0440123{col 41}{space 1}    7.87{col 50}{space 3}0.000{col 58}{space 4} .2602667{col 71}{space 3} .4327917
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2422793{col 30}{space 2} .0962715{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0535907{col 71}{space 3} .4309679
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0983312{col 30}{space 2} .0746049{col 41}{space 1}    1.32{col 50}{space 3}0.187{col 58}{space 4}-.0478916{col 71}{space 3} .2445541
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2310626{col 30}{space 2} .1059337{col 41}{space 1}    2.18{col 50}{space 3}0.029{col 58}{space 4} .0234363{col 71}{space 3} .4386888
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2207883{col 30}{space 2} .0839148{col 41}{space 1}    2.63{col 50}{space 3}0.009{col 58}{space 4} .0563182{col 71}{space 3} .3852583
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1783366{col 30}{space 2} .0655485{col 41}{space 1}   -2.72{col 50}{space 3}0.007{col 58}{space 4}-.3068093{col 71}{space 3} -.049864
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  -.12748{col 30}{space 2} .0452289{col 41}{space 1}   -2.82{col 50}{space 3}0.005{col 58}{space 4}-.2161269{col 71}{space 3} -.038833
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0012235{col 30}{space 2} .0015834{col 41}{space 1}   -0.77{col 50}{space 3}0.440{col 58}{space 4} -.004327{col 71}{space 3}   .00188
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2034678{col 30}{space 2} .2171383{col 41}{space 1}    0.94{col 50}{space 3}0.349{col 58}{space 4}-.2221155{col 71}{space 3}  .629051
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1101917{col 30}{space 2} .1187419{col 41}{space 1}    0.93{col 50}{space 3}0.353{col 58}{space 4}-.1225382{col 71}{space 3} .3429216
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}   .33457{col 30}{space 2} .0919073{col 41}{space 1}    3.64{col 50}{space 3}0.000{col 58}{space 4}  .154435{col 71}{space 3}  .514705
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5092648{col 30}{space 2} .1241275{col 41}{space 1}    4.10{col 50}{space 3}0.000{col 58}{space 4} .2659795{col 71}{space 3} .7525502
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1855409{col 30}{space 2} .1037084{col 41}{space 1}    1.79{col 50}{space 3}0.074{col 58}{space 4}-.0177238{col 71}{space 3} .3888056
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4429435{col 30}{space 2} .0810433{col 41}{space 1}    5.47{col 50}{space 3}0.000{col 58}{space 4} .2841016{col 71}{space 3} .6017854
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2722478{col 30}{space 2}  .039394{col 41}{space 1}   -6.91{col 50}{space 3}0.000{col 58}{space 4}-.3494587{col 71}{space 3}-.1950369
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2577575{col 30}{space 2} .0363371{col 41}{space 1}    7.09{col 50}{space 3}0.000{col 58}{space 4} .1865381{col 71}{space 3} .3289769
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}   4.5585{col 30}{space 2}  .107879{col 41}{space 1}   42.26{col 50}{space 3}0.000{col 58}{space 4} 4.347061{col 71}{space 3} 4.769939
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .61793953
         {txt}sigma_e {c |} {res} 1.3703359
             {txt}rho {c |} {res} .16898455{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. rename  pdd9_3      pdd9_4
{res}{txt}
{com}. rename  pdd9_2        pdd9_3
{res}{txt}
{com}. xtreg hdd9  pdd9_3    $xlist  no_species_mean $year_NIGER if country==1, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,046
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,069

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0443                                         {txt}min = {res}         1
{txt}     between = {res}0.2381                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1925                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1604.96
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_3 {c |}{col 18}{res}{space 2} .1402652{col 30}{space 2} .0176414{col 41}{space 1}    7.95{col 50}{space 3}0.000{col 58}{space 4} .1056887{col 71}{space 3} .1748418
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0143472{col 30}{space 2} .0064858{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0016353{col 71}{space 3} .0270591
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0394669{col 30}{space 2} .0962628{col 41}{space 1}   -0.41{col 50}{space 3}0.682{col 58}{space 4}-.2281385{col 71}{space 3} .1492047
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0029258{col 30}{space 2} .0013876{col 41}{space 1}    2.11{col 50}{space 3}0.035{col 58}{space 4} .0002061{col 71}{space 3} .0056455
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1077797{col 30}{space 2} .0577617{col 41}{space 1}    1.87{col 50}{space 3}0.062{col 58}{space 4}-.0054312{col 71}{space 3} .2209906
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3395085{col 30}{space 2} .0440964{col 41}{space 1}    7.70{col 50}{space 3}0.000{col 58}{space 4} .2530812{col 71}{space 3} .4259357
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2458747{col 30}{space 2} .0966195{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4}  .056504{col 71}{space 3} .4352454
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0926715{col 30}{space 2} .0743259{col 41}{space 1}    1.25{col 50}{space 3}0.212{col 58}{space 4}-.0530046{col 71}{space 3} .2383477
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2137803{col 30}{space 2} .1067788{col 41}{space 1}    2.00{col 50}{space 3}0.045{col 58}{space 4} .0044977{col 71}{space 3} .4230629
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2020572{col 30}{space 2} .0848793{col 41}{space 1}    2.38{col 50}{space 3}0.017{col 58}{space 4} .0356969{col 71}{space 3} .3684176
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1981656{col 30}{space 2} .0654339{col 41}{space 1}   -3.03{col 50}{space 3}0.002{col 58}{space 4}-.3264137{col 71}{space 3}-.0699175
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1329074{col 30}{space 2} .0450631{col 41}{space 1}   -2.95{col 50}{space 3}0.003{col 58}{space 4}-.2212295{col 71}{space 3}-.0445853
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0014096{col 30}{space 2} .0015982{col 41}{space 1}   -0.88{col 50}{space 3}0.378{col 58}{space 4} -.004542{col 71}{space 3} .0017227
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1490097{col 30}{space 2} .2200744{col 41}{space 1}    0.68{col 50}{space 3}0.498{col 58}{space 4}-.2823283{col 71}{space 3} .5803477
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1072688{col 30}{space 2} .1187873{col 41}{space 1}    0.90{col 50}{space 3}0.367{col 58}{space 4}  -.12555{col 71}{space 3} .3400876
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3380503{col 30}{space 2} .0917087{col 41}{space 1}    3.69{col 50}{space 3}0.000{col 58}{space 4} .1583045{col 71}{space 3}  .517796
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .524161{col 30}{space 2} .1249025{col 41}{space 1}    4.20{col 50}{space 3}0.000{col 58}{space 4} .2793567{col 71}{space 3} .7689653
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2022936{col 30}{space 2} .1044315{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-.0023883{col 71}{space 3} .4069755
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .460175{col 30}{space 2} .0809448{col 41}{space 1}    5.69{col 50}{space 3}0.000{col 58}{space 4} .3015262{col 71}{space 3} .6188239
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} -.155864{col 30}{space 2} .0199988{col 41}{space 1}   -7.79{col 50}{space 3}0.000{col 58}{space 4}-.1950609{col 71}{space 3}-.1166672
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2440088{col 30}{space 2} .0363028{col 41}{space 1}    6.72{col 50}{space 3}0.000{col 58}{space 4} .1728566{col 71}{space 3} .3151609
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.572957{col 30}{space 2} .1047694{col 41}{space 1}   43.65{col 50}{space 3}0.000{col 58}{space 4} 4.367613{col 71}{space 3} 4.778302
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .62305345
         {txt}sigma_e {c |} {res} 1.3666293
             {txt}rho {c |} {res} .17208235{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est8
{txt}
{com}. 
. 
. *Nigeria
. xtreg hdd9  pdd9_4    $xlist  pdd9_mean $year_NIGERIA if country==2, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    18,592
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,222

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0392                                         {txt}min = {res}         1
{txt}     between = {res}0.3100                                         {txt}avg = {res}       2.3
{txt}     overall = {res}0.2618                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  4916.63
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,222} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_4 {c |}{col 18}{res}{space 2} .0954555{col 30}{space 2} .0142286{col 41}{space 1}    6.71{col 50}{space 3}0.000{col 58}{space 4}  .067568{col 71}{space 3} .1233431
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0251421{col 30}{space 2} .0044371{col 41}{space 1}   -5.67{col 50}{space 3}0.000{col 58}{space 4}-.0338386{col 71}{space 3}-.0164456
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1374149{col 30}{space 2} .0489552{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0414646{col 71}{space 3} .2333653
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0045327{col 30}{space 2} .0009018{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .0027652{col 71}{space 3} .0063002
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2208006{col 30}{space 2} .0350994{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4} .1520071{col 71}{space 3} .2895942
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1965188{col 30}{space 2} .0272426{col 41}{space 1}    7.21{col 50}{space 3}0.000{col 58}{space 4} .1431244{col 71}{space 3} .2499132
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0383009{col 30}{space 2} .0383457{col 41}{space 1}    1.00{col 50}{space 3}0.318{col 58}{space 4}-.0368553{col 71}{space 3}  .113457
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1851155{col 30}{space 2} .0383103{col 41}{space 1}    4.83{col 50}{space 3}0.000{col 58}{space 4} .1100287{col 71}{space 3} .2602023
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0875706{col 30}{space 2}  .044639{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4} .0000796{col 71}{space 3} .1750615
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2121287{col 30}{space 2} .0480928{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .1178685{col 71}{space 3}  .306389
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2779439{col 30}{space 2} .0389845{col 41}{space 1}    7.13{col 50}{space 3}0.000{col 58}{space 4} .2015356{col 71}{space 3} .3543521
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0071558{col 30}{space 2} .0466389{col 41}{space 1}   -0.15{col 50}{space 3}0.878{col 58}{space 4}-.0985664{col 71}{space 3} .0842548
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0099185{col 30}{space 2} .0068981{col 41}{space 1}   -1.44{col 50}{space 3}0.150{col 58}{space 4}-.0234386{col 71}{space 3} .0036016
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .322513{col 30}{space 2} .0598252{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .2052577{col 71}{space 3} .4397683
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0593143{col 30}{space 2}  .053329{col 41}{space 1}   -1.11{col 50}{space 3}0.266{col 58}{space 4}-.1638371{col 71}{space 3} .0452086
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8210809{col 30}{space 2} .0585002{col 41}{space 1}   14.04{col 50}{space 3}0.000{col 58}{space 4} .7064227{col 71}{space 3} .9357391
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8517745{col 30}{space 2} .0574237{col 41}{space 1}   14.83{col 50}{space 3}0.000{col 58}{space 4} .7392261{col 71}{space 3} .9643228
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2504516{col 30}{space 2}  .063917{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .1251765{col 71}{space 3} .3757267
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0103826{col 30}{space 2} .0511221{col 41}{space 1}   -0.20{col 50}{space 3}0.839{col 58}{space 4}-.1105801{col 71}{space 3} .0898149
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0772695{col 30}{space 2} .0182096{col 41}{space 1}   -4.24{col 50}{space 3}0.000{col 58}{space 4}-.1129598{col 71}{space 3}-.0415793
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5884686{col 30}{space 2} .0307655{col 41}{space 1}  -19.13{col 50}{space 3}0.000{col 58}{space 4}-.6487679{col 71}{space 3}-.5281693
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4917889{col 30}{space 2}  .031016{col 41}{space 1}  -15.86{col 50}{space 3}0.000{col 58}{space 4}-.5525792{col 71}{space 3}-.4309987
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3387276{col 30}{space 2} .0305652{col 41}{space 1}  -11.08{col 50}{space 3}0.000{col 58}{space 4}-.3986343{col 71}{space 3}-.2788209
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.524212{col 30}{space 2} .0744022{col 41}{space 1}   60.81{col 50}{space 3}0.000{col 58}{space 4} 4.378386{col 71}{space 3} 4.670037
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .85893868
         {txt}sigma_e {c |} {res} 1.2348383
             {txt}rho {c |} {res} .32607409{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est9
{txt}
{com}. rename  pdd9_4       pdd9_5
{res}{txt}
{com}. rename  pdd9_3       pdd9_4
{res}{txt}
{com}. xtreg hdd9  pdd9_4    $xlist  no_species_mean $year_NIGERIA if country==2, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    18,592
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,222

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0392                                         {txt}min = {res}         1
{txt}     between = {res}0.3106                                         {txt}avg = {res}       2.3
{txt}     overall = {res}0.2617                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  4908.63
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,222} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_4 {c |}{col 18}{res}{space 2} .0471703{col 30}{space 2} .0081724{col 41}{space 1}    5.77{col 50}{space 3}0.000{col 58}{space 4} .0311527{col 71}{space 3} .0631879
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.020121{col 30}{space 2} .0044888{col 41}{space 1}   -4.48{col 50}{space 3}0.000{col 58}{space 4}-.0289188{col 71}{space 3}-.0113231
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1331588{col 30}{space 2} .0489675{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0371842{col 71}{space 3} .2291334
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0049115{col 30}{space 2}    .0009{col 41}{space 1}    5.46{col 50}{space 3}0.000{col 58}{space 4} .0031475{col 71}{space 3} .0066755
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2093415{col 30}{space 2} .0352523{col 41}{space 1}    5.94{col 50}{space 3}0.000{col 58}{space 4} .1402483{col 71}{space 3} .2784348
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1934741{col 30}{space 2} .0272279{col 41}{space 1}    7.11{col 50}{space 3}0.000{col 58}{space 4} .1401084{col 71}{space 3} .2468398
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0342251{col 30}{space 2} .0383678{col 41}{space 1}    0.89{col 50}{space 3}0.372{col 58}{space 4}-.0409744{col 71}{space 3} .1094247
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1843987{col 30}{space 2} .0382266{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .1094759{col 71}{space 3} .2593214
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0881066{col 30}{space 2} .0445719{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4} .0007474{col 71}{space 3} .1754659
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2083799{col 30}{space 2} .0481205{col 41}{space 1}    4.33{col 50}{space 3}0.000{col 58}{space 4} .1140654{col 71}{space 3} .3026944
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2754478{col 30}{space 2} .0390961{col 41}{space 1}    7.05{col 50}{space 3}0.000{col 58}{space 4} .1988208{col 71}{space 3} .3520747
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0062967{col 30}{space 2} .0467175{col 41}{space 1}    0.13{col 50}{space 3}0.893{col 58}{space 4} -.085268{col 71}{space 3} .0978614
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.006907{col 30}{space 2} .0060128{col 41}{space 1}   -1.15{col 50}{space 3}0.251{col 58}{space 4}-.0186918{col 71}{space 3} .0048779
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3312306{col 30}{space 2} .0604439{col 41}{space 1}    5.48{col 50}{space 3}0.000{col 58}{space 4} .2127627{col 71}{space 3} .4496985
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0114003{col 30}{space 2} .0531208{col 41}{space 1}   -0.21{col 50}{space 3}0.830{col 58}{space 4}-.1155151{col 71}{space 3} .0927144
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8015068{col 30}{space 2} .0585994{col 41}{space 1}   13.68{col 50}{space 3}0.000{col 58}{space 4}  .686654{col 71}{space 3} .9163595
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7937102{col 30}{space 2} .0576417{col 41}{space 1}   13.77{col 50}{space 3}0.000{col 58}{space 4} .6807345{col 71}{space 3} .9066859
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2169979{col 30}{space 2} .0637748{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .0920017{col 71}{space 3} .3419942
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0234546{col 30}{space 2} .0511102{col 41}{space 1}   -0.46{col 50}{space 3}0.646{col 58}{space 4}-.1236287{col 71}{space 3} .0767195
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0729979{col 30}{space 2} .0104846{col 41}{space 1}   -6.96{col 50}{space 3}0.000{col 58}{space 4}-.0935472{col 71}{space 3}-.0524485
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5991942{col 30}{space 2} .0306746{col 41}{space 1}  -19.53{col 50}{space 3}0.000{col 58}{space 4}-.6593153{col 71}{space 3} -.539073
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.506705{col 30}{space 2} .0308954{col 41}{space 1}  -16.40{col 50}{space 3}0.000{col 58}{space 4}-.5672589{col 71}{space 3}-.4461511
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3506558{col 30}{space 2} .0303754{col 41}{space 1}  -11.54{col 50}{space 3}0.000{col 58}{space 4}-.4101904{col 71}{space 3}-.2911211
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.644306{col 30}{space 2} .0743304{col 41}{space 1}   62.48{col 50}{space 3}0.000{col 58}{space 4} 4.498621{col 71}{space 3} 4.789991
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .85797448
         {txt}sigma_e {c |} {res} 1.2351846
             {txt}rho {c |} {res} .32545753{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est10
{txt}
{com}. 
. 
. 
. *Tanzania
. xtreg hdd9  pdd9_5    $xlist  pdd9_mean $year_TANZANIA if country==5, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    21,117
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,363

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0310                                         {txt}min = {res}         1
{txt}     between = {res}0.2176                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1877                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3822.97
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,363} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_5 {c |}{col 18}{res}{space 2} .1439935{col 30}{space 2} .0108076{col 41}{space 1}   13.32{col 50}{space 3}0.000{col 58}{space 4} .1228109{col 71}{space 3} .1651761
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0044703{col 30}{space 2} .0042332{col 41}{space 1}   -1.06{col 50}{space 3}0.291{col 58}{space 4}-.0127672{col 71}{space 3} .0038267
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0888128{col 30}{space 2} .0507284{col 41}{space 1}    1.75{col 50}{space 3}0.080{col 58}{space 4}-.0106129{col 71}{space 3} .1882386
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0008937{col 30}{space 2} .0008185{col 41}{space 1}   -1.09{col 50}{space 3}0.275{col 58}{space 4} -.002498{col 71}{space 3} .0007105
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0700597{col 30}{space 2} .0276496{col 41}{space 1}    2.53{col 50}{space 3}0.011{col 58}{space 4} .0158676{col 71}{space 3} .1242518
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3105817{col 30}{space 2} .0286183{col 41}{space 1}   10.85{col 50}{space 3}0.000{col 58}{space 4} .2544909{col 71}{space 3} .3666725
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1684405{col 30}{space 2} .0590209{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0527616{col 71}{space 3} .2841193
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3013008{col 30}{space 2} .0395684{col 41}{space 1}    7.61{col 50}{space 3}0.000{col 58}{space 4} .2237481{col 71}{space 3} .3788534
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0785698{col 30}{space 2} .0425272{col 41}{space 1}    1.85{col 50}{space 3}0.065{col 58}{space 4} -.004782{col 71}{space 3} .1619217
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1313993{col 30}{space 2} .0298078{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .0729771{col 71}{space 3} .1898215
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .257655{col 30}{space 2} .0315578{col 41}{space 1}    8.16{col 50}{space 3}0.000{col 58}{space 4} .1958028{col 71}{space 3} .3195073
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1510342{col 30}{space 2} .0265906{col 41}{space 1}   -5.68{col 50}{space 3}0.000{col 58}{space 4}-.2031508{col 71}{space 3}-.0989176
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0021208{col 30}{space 2} .0019355{col 41}{space 1}    1.10{col 50}{space 3}0.273{col 58}{space 4}-.0016726{col 71}{space 3} .0059142
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0101063{col 30}{space 2} .0282273{col 41}{space 1}    0.36{col 50}{space 3}0.720{col 58}{space 4}-.0452182{col 71}{space 3} .0654308
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .5031243{col 30}{space 2} .0760903{col 41}{space 1}    6.61{col 50}{space 3}0.000{col 58}{space 4} .3539901{col 71}{space 3} .6522586
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4077521{col 30}{space 2} .0538653{col 41}{space 1}    7.57{col 50}{space 3}0.000{col 58}{space 4} .3021781{col 71}{space 3} .5133261
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5488096{col 30}{space 2} .0548292{col 41}{space 1}   10.01{col 50}{space 3}0.000{col 58}{space 4} .4413464{col 71}{space 3} .6562728
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1183783{col 30}{space 2} .0424295{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4}  .035218{col 71}{space 3} .2015386
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2360312{col 30}{space 2} .0434985{col 41}{space 1}    5.43{col 50}{space 3}0.000{col 58}{space 4} .1507757{col 71}{space 3} .3212867
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1016559{col 30}{space 2} .0130001{col 41}{space 1}   -7.82{col 50}{space 3}0.000{col 58}{space 4}-.1271357{col 71}{space 3}-.0761762
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0775034{col 30}{space 2} .0289879{col 41}{space 1}    2.67{col 50}{space 3}0.008{col 58}{space 4} .0206881{col 71}{space 3} .1343187
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0950504{col 30}{space 2} .0242958{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4} .0474315{col 71}{space 3} .1426692
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .1098999{col 30}{space 2} .0270916{col 41}{space 1}    4.06{col 50}{space 3}0.000{col 58}{space 4} .0568015{col 71}{space 3} .1629984
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.368412{col 30}{space 2}  .063433{col 41}{space 1}   68.87{col 50}{space 3}0.000{col 58}{space 4} 4.244085{col 71}{space 3} 4.492738
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .79869839
         {txt}sigma_e {c |} {res} 1.2448832
             {txt}rho {c |} {res} .29159972{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est11
{txt}
{com}. rename  pdd9_5       pdd9_6
{res}{txt}
{com}. rename  pdd9_4       pdd9_5
{res}{txt}
{com}. xtreg hdd9  pdd9_5    $xlist  no_species_mean $year_TANZANIA if country==5, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    21,117
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,363

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0244                                         {txt}min = {res}         1
{txt}     between = {res}0.2175                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1863                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3757.04
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,363} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_5 {c |}{col 18}{res}{space 2} .0576956{col 30}{space 2} .0055906{col 41}{space 1}   10.32{col 50}{space 3}0.000{col 58}{space 4} .0467383{col 71}{space 3} .0686529
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0049955{col 30}{space 2}  .004237{col 41}{space 1}   -1.18{col 50}{space 3}0.238{col 58}{space 4}-.0132998{col 71}{space 3} .0033089
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .099483{col 30}{space 2}  .050736{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4} .0000424{col 71}{space 3} .1989237
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0011434{col 30}{space 2} .0008232{col 41}{space 1}   -1.39{col 50}{space 3}0.165{col 58}{space 4}-.0027569{col 71}{space 3} .0004701
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0697969{col 30}{space 2} .0276441{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0156155{col 71}{space 3} .1239784
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3057733{col 30}{space 2} .0286156{col 41}{space 1}   10.69{col 50}{space 3}0.000{col 58}{space 4} .2496877{col 71}{space 3} .3618589
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1841884{col 30}{space 2} .0592742{col 41}{space 1}    3.11{col 50}{space 3}0.002{col 58}{space 4}  .068013{col 71}{space 3} .3003637
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .307486{col 30}{space 2} .0396454{col 41}{space 1}    7.76{col 50}{space 3}0.000{col 58}{space 4} .2297825{col 71}{space 3} .3851896
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0811673{col 30}{space 2} .0426106{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0023479{col 71}{space 3} .1646826
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1335962{col 30}{space 2}  .029948{col 41}{space 1}    4.46{col 50}{space 3}0.000{col 58}{space 4} .0748993{col 71}{space 3} .1922932
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2595765{col 30}{space 2} .0316425{col 41}{space 1}    8.20{col 50}{space 3}0.000{col 58}{space 4} .1975583{col 71}{space 3} .3215947
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1488398{col 30}{space 2} .0266399{col 41}{space 1}   -5.59{col 50}{space 3}0.000{col 58}{space 4}-.2010532{col 71}{space 3}-.0966265
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0019937{col 30}{space 2} .0019771{col 41}{space 1}    1.01{col 50}{space 3}0.313{col 58}{space 4}-.0018814{col 71}{space 3} .0058688
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0627476{col 30}{space 2} .0306755{col 41}{space 1}   -2.05{col 50}{space 3}0.041{col 58}{space 4}-.1228706{col 71}{space 3}-.0026247
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4859705{col 30}{space 2} .0762218{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .3365785{col 71}{space 3} .6353625
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4016056{col 30}{space 2} .0538522{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .2960573{col 71}{space 3}  .507154
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5470101{col 30}{space 2} .0545815{col 41}{space 1}   10.02{col 50}{space 3}0.000{col 58}{space 4} .4400323{col 71}{space 3} .6539878
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1189543{col 30}{space 2} .0424438{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4}  .035766{col 71}{space 3} .2021427
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2377005{col 30}{space 2} .0435131{col 41}{space 1}    5.46{col 50}{space 3}0.000{col 58}{space 4} .1524164{col 71}{space 3} .3229846
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0291547{col 30}{space 2} .0065248{col 41}{space 1}   -4.47{col 50}{space 3}0.000{col 58}{space 4}-.0419431{col 71}{space 3}-.0163662
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0951978{col 30}{space 2} .0289431{col 41}{space 1}    3.29{col 50}{space 3}0.001{col 58}{space 4} .0384704{col 71}{space 3} .1519252
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0944423{col 30}{space 2} .0243487{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4} .0467198{col 71}{space 3} .1421648
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .1118864{col 30}{space 2} .0272184{col 41}{space 1}    4.11{col 50}{space 3}0.000{col 58}{space 4} .0585393{col 71}{space 3} .1652335
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.379884{col 30}{space 2} .0619963{col 41}{space 1}   70.65{col 50}{space 3}0.000{col 58}{space 4} 4.258373{col 71}{space 3} 4.501394
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7949824
         {txt}sigma_e {c |} {res} 1.2490973
             {txt}rho {c |} {res} .28828811{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est12
{txt}
{com}. 
. 
. 
. *Uganda
. xtreg hdd9  pdd9_6    $xlist  pdd9_mean $year_UGANDA if country==4, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    20,313
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,107

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0480                                         {txt}min = {res}         1
{txt}     between = {res}0.2727                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.1889                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  2986.99
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,107} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_6 {c |}{col 18}{res}{space 2}   .09694{col 30}{space 2} .0099922{col 41}{space 1}    9.70{col 50}{space 3}0.000{col 58}{space 4} .0773555{col 71}{space 3} .1165244
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0151554{col 30}{space 2} .0051749{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .0050128{col 71}{space 3} .0252979
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1504517{col 30}{space 2} .0552696{col 41}{space 1}    2.72{col 50}{space 3}0.006{col 58}{space 4} .0421252{col 71}{space 3} .2587781
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0015235{col 30}{space 2} .0009812{col 41}{space 1}   -1.55{col 50}{space 3}0.121{col 58}{space 4}-.0034467{col 71}{space 3} .0003997
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0672678{col 30}{space 2} .0317513{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0050365{col 71}{space 3} .1294991
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2662947{col 30}{space 2} .0313285{col 41}{space 1}    8.50{col 50}{space 3}0.000{col 58}{space 4}  .204892{col 71}{space 3} .3276975
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2268061{col 30}{space 2} .0499062{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .1289917{col 71}{space 3} .3246204
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2537338{col 30}{space 2} .0338444{col 41}{space 1}    7.50{col 50}{space 3}0.000{col 58}{space 4}    .1874{col 71}{space 3} .3200675
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3387038{col 30}{space 2} .0340837{col 41}{space 1}    9.94{col 50}{space 3}0.000{col 58}{space 4}  .271901{col 71}{space 3} .4055065
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .061065{col 30}{space 2} .0276843{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0068048{col 71}{space 3} .1153253
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1937012{col 30}{space 2} .0283854{col 41}{space 1}    6.82{col 50}{space 3}0.000{col 58}{space 4} .1380668{col 71}{space 3} .2493355
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0151502{col 30}{space 2} .0235394{col 41}{space 1}   -0.64{col 50}{space 3}0.520{col 58}{space 4}-.0612866{col 71}{space 3} .0309861
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0013121{col 30}{space 2} .0011844{col 41}{space 1}    1.11{col 50}{space 3}0.268{col 58}{space 4}-.0010094{col 71}{space 3} .0036335
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0072006{col 30}{space 2} .0266275{col 41}{space 1}   -0.27{col 50}{space 3}0.787{col 58}{space 4}-.0593896{col 71}{space 3} .0449884
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2215519{col 30}{space 2} .0800534{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4} .0646501{col 71}{space 3} .3784537
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3981731{col 30}{space 2}  .059736{col 41}{space 1}    6.67{col 50}{space 3}0.000{col 58}{space 4} .2810926{col 71}{space 3} .5152536
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4967286{col 30}{space 2} .0640024{col 41}{space 1}    7.76{col 50}{space 3}0.000{col 58}{space 4} .3712863{col 71}{space 3}  .622171
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1516256{col 30}{space 2} .0529747{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4}  .047797{col 71}{space 3} .2554541
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3567216{col 30}{space 2} .0511623{col 41}{space 1}    6.97{col 50}{space 3}0.000{col 58}{space 4} .2564454{col 71}{space 3} .4569978
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0070907{col 30}{space 2} .0149307{col 41}{space 1}   -0.47{col 50}{space 3}0.635{col 58}{space 4}-.0363543{col 71}{space 3} .0221729
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1668303{col 30}{space 2} .0323825{col 41}{space 1}   -5.15{col 50}{space 3}0.000{col 58}{space 4}-.2302988{col 71}{space 3}-.1033617
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0543754{col 30}{space 2} .0304832{col 41}{space 1}   -1.78{col 50}{space 3}0.074{col 58}{space 4}-.1141213{col 71}{space 3} .0053705
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3287094{col 30}{space 2} .0308382{col 41}{space 1}   10.66{col 50}{space 3}0.000{col 58}{space 4} .2682676{col 71}{space 3} .3891513
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0733056{col 30}{space 2} .0306156{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0133001{col 71}{space 3} .1333111
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2759902{col 30}{space 2}  .029117{col 41}{space 1}    9.48{col 50}{space 3}0.000{col 58}{space 4} .2189219{col 71}{space 3} .3330585
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.963684{col 30}{space 2} .0822749{col 41}{space 1}   48.18{col 50}{space 3}0.000{col 58}{space 4} 3.802428{col 71}{space 3}  4.12494
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .8641309
         {txt}sigma_e {c |} {res} 1.2834766
             {txt}rho {c |} {res} .31190954{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est13
{txt}
{com}. drop    pdd9_6
{txt}
{com}. rename  pdd9_5       pdd9_6
{res}{txt}
{com}. xtreg hdd9  pdd9_6    $xlist  no_species_mean $year_UGANDA if country==4, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    20,313
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,107

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0464                                         {txt}min = {res}         1
{txt}     between = {res}0.2713                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.1877                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  2946.35
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,107} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_6 {c |}{col 18}{res}{space 2}  .047658{col 30}{space 2} .0054543{col 41}{space 1}    8.74{col 50}{space 3}0.000{col 58}{space 4} .0369678{col 71}{space 3} .0583482
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0147358{col 30}{space 2} .0052129{col 41}{space 1}    2.83{col 50}{space 3}0.005{col 58}{space 4} .0045187{col 71}{space 3} .0249528
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1616278{col 30}{space 2} .0553579{col 41}{space 1}    2.92{col 50}{space 3}0.004{col 58}{space 4} .0531282{col 71}{space 3} .2701274
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0014277{col 30}{space 2} .0009858{col 41}{space 1}   -1.45{col 50}{space 3}0.148{col 58}{space 4}-.0033598{col 71}{space 3} .0005044
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0665107{col 30}{space 2} .0318214{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0041419{col 71}{space 3} .1288796
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2659529{col 30}{space 2} .0314226{col 41}{space 1}    8.46{col 50}{space 3}0.000{col 58}{space 4} .2043657{col 71}{space 3} .3275401
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2268858{col 30}{space 2}  .050048{col 41}{space 1}    4.53{col 50}{space 3}0.000{col 58}{space 4} .1287934{col 71}{space 3} .3249782
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .257494{col 30}{space 2} .0338828{col 41}{space 1}    7.60{col 50}{space 3}0.000{col 58}{space 4}  .191085{col 71}{space 3} .3239031
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3541301{col 30}{space 2} .0342232{col 41}{space 1}   10.35{col 50}{space 3}0.000{col 58}{space 4} .2870538{col 71}{space 3} .4212063
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .059779{col 30}{space 2} .0276811{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0055251{col 71}{space 3}  .114033
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1891433{col 30}{space 2} .0284118{col 41}{space 1}    6.66{col 50}{space 3}0.000{col 58}{space 4} .1334573{col 71}{space 3} .2448294
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0168306{col 30}{space 2} .0236343{col 41}{space 1}   -0.71{col 50}{space 3}0.476{col 58}{space 4}-.0631531{col 71}{space 3} .0294918
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0011719{col 30}{space 2} .0011988{col 41}{space 1}    0.98{col 50}{space 3}0.328{col 58}{space 4}-.0011778{col 71}{space 3} .0035216
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0520941{col 30}{space 2}   .02815{col 41}{space 1}   -1.85{col 50}{space 3}0.064{col 58}{space 4}-.1072671{col 71}{space 3} .0030788
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2273368{col 30}{space 2} .0799668{col 41}{space 1}    2.84{col 50}{space 3}0.004{col 58}{space 4} .0706048{col 71}{space 3} .3840688
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .398057{col 30}{space 2} .0598042{col 41}{space 1}    6.66{col 50}{space 3}0.000{col 58}{space 4}  .280843{col 71}{space 3}  .515271
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4687039{col 30}{space 2}  .064228{col 41}{space 1}    7.30{col 50}{space 3}0.000{col 58}{space 4} .3428193{col 71}{space 3} .5945885
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1472851{col 30}{space 2} .0530634{col 41}{space 1}    2.78{col 50}{space 3}0.006{col 58}{space 4} .0432827{col 71}{space 3} .2512875
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3479567{col 30}{space 2} .0510073{col 41}{space 1}    6.82{col 50}{space 3}0.000{col 58}{space 4} .2479842{col 71}{space 3} .4479293
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0007071{col 30}{space 2} .0076852{col 41}{space 1}   -0.09{col 50}{space 3}0.927{col 58}{space 4}-.0157698{col 71}{space 3} .0143556
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1873422{col 30}{space 2} .0323652{col 41}{space 1}   -5.79{col 50}{space 3}0.000{col 58}{space 4}-.2507769{col 71}{space 3}-.1239076
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0527764{col 30}{space 2} .0304618{col 41}{space 1}   -1.73{col 50}{space 3}0.083{col 58}{space 4}-.1124804{col 71}{space 3} .0069275
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3545908{col 30}{space 2} .0308456{col 41}{space 1}   11.50{col 50}{space 3}0.000{col 58}{space 4} .2941345{col 71}{space 3} .4150471
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0892875{col 30}{space 2} .0306335{col 41}{space 1}    2.91{col 50}{space 3}0.004{col 58}{space 4}  .029247{col 71}{space 3}  .149328
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2966267{col 30}{space 2} .0291994{col 41}{space 1}   10.16{col 50}{space 3}0.000{col 58}{space 4}  .239397{col 71}{space 3} .3538564
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.002872{col 30}{space 2} .0800372{col 41}{space 1}   50.01{col 50}{space 3}0.000{col 58}{space 4} 3.846002{col 71}{space 3} 4.159742
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .86524939
         {txt}sigma_e {c |} {res} 1.2845376
             {txt}rho {c |} {res} .31211014{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est14
{txt}
{com}. 
. 
. coefplot (est1, label("Farm production diversity (food group count)") msymbol(d) mlcolor(red%80) mfcolor(white)    ) (est2, label("") msymbol(s) mcolor(navy) mfcolor(white)  )    (est3, label("")  msymbol(d) mlcolor(red%80) mfcolor(white) ) (est4, label("") msymbol(s) mcolor(navy) mfcolor(white)  ) ///    
>  (est5,label("") msymbol(d) mlcolor(red%80) mfcolor(white)) (est6,  label("") msymbol(s) mcolor(navy) mfcolor(white)  )   (est7, label("") msymbol(d) mlcolor(red%80) mfcolor(white)  )  (est8, label("Farm production diversity (species count)") msymbol(s) mcolor(navy) mfcolor(white)  ) /// 
>  (est9, label("") msymbol(d) mlcolor(red%80) mfcolor(white)) (est10, label("") msymbol(s) mcolor(navy) mfcolor(white)  )   (est11, label("") msymbol(d) mlcolor(red%80) mfcolor(white)  )  (est12, label("") msymbol(s) mcolor(navy) mfcolor(white)  ) /// 
>  (est13, label("") msymbol(d) mlcolor(red%80) mfcolor(white) ) (est14,label("")  msymbol(s) mcolor(navy) mfcolor(white)  )  /// 
> ,  byopts(xrescale) keep(pdd9 pdd9_1 pdd9_2 pdd9_3  pdd9_4 pdd9_5 pdd9_6) vertical ciopts(lcolor(grey) color(%50)  recast(rcap))  /// 
> legend(  size(small) rows(2) nobox region(color(white) lstyle(white))) ///  
> xlabel(1 "All countries" 2 "Ethiopia" 3 "Malawi" 4 "Niger"    5 "Nigeria" 6 "Tanzania" 7 "Uganda" , labsize(small))   /// 
>   ytitle("HDDS", size(small)) levels(95)  plotregion(margin(0)) offset(0)
{res}{p 0 4 2}
{txt}(note:  named style
0 not found in class
margin,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
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color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
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color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
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{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
white not found in class
linestyle,  default attributes used)
{p_end}
{res}{txt}
{com}. graph save "Figure_1_Impacts_FGPRD_SCPD.gph", replace
{res}{txt}(file Figure_1_Impacts_FGPRD_SCPD.gph saved)

{com}. restore 
{txt}
{com}. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                  Figure 2_Determinants_Pooled_All Factors                    *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9   $xlist  pdd9_mean i.country i.year  , cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    89,742
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    36,644

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0290                                         {txt}min = {res}         1
{txt}     between = {res}0.3561                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2856                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 27347.26
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:36,644} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .100046{col 30}{space 2} .0051959{col 41}{space 1}   19.25{col 50}{space 3}0.000{col 58}{space 4} .0898622{col 71}{space 3} .1102297
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0030401{col 30}{space 2} .0022275{col 41}{space 1}   -1.36{col 50}{space 3}0.172{col 58}{space 4} -.007406{col 71}{space 3} .0013258
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .065032{col 30}{space 2}   .02411{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .0177772{col 71}{space 3} .1122868
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0004217{col 30}{space 2}   .00041{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.0003818{col 71}{space 3} .0012253
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0496982{col 30}{space 2} .0143935{col 41}{space 1}    3.45{col 50}{space 3}0.001{col 58}{space 4} .0214874{col 71}{space 3}  .077909
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3002783{col 30}{space 2} .0134006{col 41}{space 1}   22.41{col 50}{space 3}0.000{col 58}{space 4} .2740137{col 71}{space 3} .3265429
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1228612{col 30}{space 2} .0252171{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .0734365{col 71}{space 3} .1722858
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2169943{col 30}{space 2} .0173222{col 41}{space 1}   12.53{col 50}{space 3}0.000{col 58}{space 4} .1830434{col 71}{space 3} .2509452
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1804894{col 30}{space 2}  .019958{col 41}{space 1}    9.04{col 50}{space 3}0.000{col 58}{space 4} .1413725{col 71}{space 3} .2196063
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1260233{col 30}{space 2} .0166278{col 41}{space 1}    7.58{col 50}{space 3}0.000{col 58}{space 4} .0934334{col 71}{space 3} .1586132
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2200247{col 30}{space 2} .0155761{col 41}{space 1}   14.13{col 50}{space 3}0.000{col 58}{space 4}  .189496{col 71}{space 3} .2505533
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0865284{col 30}{space 2} .0128051{col 41}{space 1}   -6.76{col 50}{space 3}0.000{col 58}{space 4} -.111626{col 71}{space 3}-.0614309
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003881{col 30}{space 2} .0009502{col 41}{space 1}    0.41{col 50}{space 3}0.683{col 58}{space 4}-.0014743{col 71}{space 3} .0022504
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0966535{col 30}{space 2} .0148938{col 41}{space 1}    6.49{col 50}{space 3}0.000{col 58}{space 4} .0674622{col 71}{space 3} .1258448
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0706861{col 30}{space 2} .0343358{col 41}{space 1}    2.06{col 50}{space 3}0.040{col 58}{space 4} .0033892{col 71}{space 3}  .137983
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5467516{col 30}{space 2} .0254487{col 41}{space 1}   21.48{col 50}{space 3}0.000{col 58}{space 4} .4968731{col 71}{space 3} .5966302
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6966126{col 30}{space 2} .0272048{col 41}{space 1}   25.61{col 50}{space 3}0.000{col 58}{space 4} .6432923{col 71}{space 3}  .749933
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .240854{col 30}{space 2}  .024667{col 41}{space 1}    9.76{col 50}{space 3}0.000{col 58}{space 4} .1925076{col 71}{space 3} .2892004
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1894021{col 30}{space 2} .0221414{col 41}{space 1}    8.55{col 50}{space 3}0.000{col 58}{space 4} .1460057{col 71}{space 3} .2327984
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0503437{col 30}{space 2} .0067234{col 41}{space 1}   -7.49{col 50}{space 3}0.000{col 58}{space 4}-.0635213{col 71}{space 3}-.0371661
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3034848{col 30}{space 2} .0295445{col 41}{space 1}  -10.27{col 50}{space 3}0.000{col 58}{space 4}-.3613909{col 71}{space 3}-.2455787
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.372043{col 30}{space 2}   .02916{col 41}{space 1}  -47.05{col 50}{space 3}0.000{col 58}{space 4}-1.429196{col 71}{space 3}-1.314891
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.3849754{col 30}{space 2} .0291919{col 41}{space 1}  -13.19{col 50}{space 3}0.000{col 58}{space 4}-.4421905{col 71}{space 3}-.3277604
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.1965689{col 30}{space 2} .0278902{col 41}{space 1}   -7.05{col 50}{space 3}0.000{col 58}{space 4}-.2512327{col 71}{space 3}-.1419051
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .6739114{col 30}{space 2} .0337996{col 41}{space 1}   19.94{col 50}{space 3}0.000{col 58}{space 4} .6076653{col 71}{space 3} .7401575
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2256059{col 30}{space 2} .0385288{col 41}{space 1}   -5.86{col 50}{space 3}0.000{col 58}{space 4} -.301121{col 71}{space 3}-.1500909
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0506931{col 30}{space 2} .0276656{col 41}{space 1}   -1.83{col 50}{space 3}0.067{col 58}{space 4}-.1049168{col 71}{space 3} .0035305
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0427377{col 30}{space 2} .0318888{col 41}{space 1}    1.34{col 50}{space 3}0.180{col 58}{space 4}-.0197632{col 71}{space 3} .1052386
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0060608{col 30}{space 2}  .028045{col 41}{space 1}    0.22{col 50}{space 3}0.829{col 58}{space 4}-.0489064{col 71}{space 3}  .061028
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0529548{col 30}{space 2}  .031712{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0091995{col 71}{space 3} .1151091
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0722623{col 30}{space 2} .0318453{col 41}{space 1}   -2.27{col 50}{space 3}0.023{col 58}{space 4} -.134678{col 71}{space 3}-.0098466
{txt}{space 11}2015  {c |}{col 18}{res}{space 2}  .143557{col 30}{space 2} .0306107{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0835611{col 71}{space 3}  .203553
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2290239{col 30}{space 2} .0424158{col 41}{space 1}   -5.40{col 50}{space 3}0.000{col 58}{space 4}-.3121573{col 71}{space 3}-.1458906
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3829816{col 30}{space 2} .0329361{col 41}{space 1}   11.63{col 50}{space 3}0.000{col 58}{space 4} .3184281{col 71}{space 3} .4475352
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0976156{col 30}{space 2} .0300959{col 41}{space 1}   -3.24{col 50}{space 3}0.001{col 58}{space 4}-.1566024{col 71}{space 3}-.0386288
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.464915{col 30}{space 2} .0458253{col 41}{space 1}   97.43{col 50}{space 3}0.000{col 58}{space 4} 4.375099{col 71}{space 3} 4.554731
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .81463678
         {txt}sigma_e {c |} {res} 1.2548029
             {txt}rho {c |} {res} .29650786{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo clear
{txt}
{com}. eststo est1
{txt}
{com}. 
. 
. coefplot (est1 , msymbol(d) msize(medlarge) mfcolor(white) mlcolor(red%80) mlwidth(medium)), xline(0) keep(pdd9 hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop  ) horizontal byopts(compact cols(1))  ///
> ylabel(1 "FPD" 2 "Household size" 3 "Dependent share" 4 "Head age"    5 "Female head" 6  "Head literacy" 7 "Motobike" ///
> 8 "Phone"  9 "Electrictity"  10 "Wage employment" 11 "Non-farm enterprise"  12 "Weather shock"  13 "Farm area"  14 "Non-food cash crop"  , nogrid labsize(small))  legend( size(small) position(6) rows(2) nobox region(color(white) lstyle(none)))  ///
>  yla( 1 (1) 14) ciopts(lcolor(black) recast(rcap        ) color(%60)) plotr(color(white)) levels(95)
{res}{txt}
{com}. graph save "Figure_2_Determinants.gph", replace
{res}{txt}(file Figure_2_Determinants.gph saved)

{com}. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *               Figure 3a_Impacts by distance to urban center                  *
. ********************************************************************************
. preserve
{txt}
{com}. drop if dist_popcenter==.
{txt}(27,826 observations deleted)

{com}. 
. drop pdd9_mean  no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. egen pdd9_mean=mean(pdd9), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_vill=mean(pdd9_vill), by(HHID_panel)
{txt}(887 missing values generated)

{com}. egen pdd9_mean_town=mean(pdd9_town), by(HHID_panel)
{txt}(839 missing values generated)

{com}. egen pdd9_mean_dist=mean(pdd9_dist), by(HHID_panel)
{txt}(837 missing values generated)

{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. 
. eststo clear
{txt}
{com}. xtreg hdd9  c.pdd9##c.dist_popcenter   $xlist  pdd9_mean  i.country i.year  , cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    61,916
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,794

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0272                                         {txt}min = {res}         1
{txt}     between = {res}0.3860                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.3180                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}35{txt})     =  {res} 22660.51
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:27,794} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0606134{col 37}{space 2} .0075023{col 48}{space 1}    8.08{col 57}{space 3}0.000{col 65}{space 4} .0459092{col 78}{space 3} .0753176
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0047496{col 37}{space 2} .0003483{col 48}{space 1}  -13.64{col 57}{space 3}0.000{col 65}{space 4}-.0054322{col 78}{space 3} -.004067
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0007449{col 37}{space 2} .0001069{col 48}{space 1}    6.97{col 57}{space 3}0.000{col 65}{space 4} .0005354{col 78}{space 3} .0009543
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2}-.0025116{col 37}{space 2} .0025756{col 48}{space 1}   -0.98{col 57}{space 3}0.329{col 65}{space 4}-.0075597{col 78}{space 3} .0025366
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2} .0751468{col 37}{space 2} .0286456{col 48}{space 1}    2.62{col 57}{space 3}0.009{col 65}{space 4} .0190025{col 78}{space 3} .1312912
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}-.0001677{col 37}{space 2} .0004776{col 48}{space 1}   -0.35{col 57}{space 3}0.725{col 65}{space 4}-.0011037{col 78}{space 3} .0007683
{txt}{space 12}female_head {c |}{col 25}{res}{space 2}  .039663{col 37}{space 2} .0172499{col 48}{space 1}    2.30{col 57}{space 3}0.021{col 65}{space 4} .0058539{col 78}{space 3} .0734722
{txt}{space 14}head_read {c |}{col 25}{res}{space 2}  .288375{col 37}{space 2}  .015346{col 48}{space 1}   18.79{col 57}{space 3}0.000{col 65}{space 4} .2582975{col 78}{space 3} .3184526
{txt}{space 15}motobike {c |}{col 25}{res}{space 2} .0660562{col 37}{space 2} .0300213{col 48}{space 1}    2.20{col 57}{space 3}0.028{col 65}{space 4} .0072156{col 78}{space 3} .1248969
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .1731451{col 37}{space 2} .0206509{col 48}{space 1}    8.38{col 57}{space 3}0.000{col 65}{space 4} .1326701{col 78}{space 3} .2136201
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .1021967{col 37}{space 2} .0276826{col 48}{space 1}    3.69{col 57}{space 3}0.000{col 65}{space 4} .0479398{col 78}{space 3} .1564536
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .1056096{col 37}{space 2} .0218033{col 48}{space 1}    4.84{col 57}{space 3}0.000{col 65}{space 4} .0628759{col 78}{space 3} .1483432
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2} .1894007{col 37}{space 2} .0203067{col 48}{space 1}    9.33{col 57}{space 3}0.000{col 65}{space 4} .1496004{col 78}{space 3}  .229201
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2} -.054551{col 37}{space 2} .0163137{col 48}{space 1}   -3.34{col 57}{space 3}0.001{col 65}{space 4}-.0865252{col 78}{space 3}-.0225768
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2} .0007793{col 37}{space 2} .0010059{col 48}{space 1}    0.77{col 57}{space 3}0.439{col 65}{space 4}-.0011923{col 78}{space 3} .0027509
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2} .1182518{col 37}{space 2}  .018633{col 48}{space 1}    6.35{col 57}{space 3}0.000{col 65}{space 4} .0817318{col 78}{space 3} .1547718
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2} .0192306{col 37}{space 2} .0402244{col 48}{space 1}    0.48{col 57}{space 3}0.633{col 65}{space 4}-.0596077{col 78}{space 3} .0980688
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .6178905{col 37}{space 2} .0293936{col 48}{space 1}   21.02{col 57}{space 3}0.000{col 65}{space 4} .5602802{col 78}{space 3} .6755008
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .7747215{col 37}{space 2} .0355541{col 48}{space 1}   21.79{col 57}{space 3}0.000{col 65}{space 4} .7050367{col 78}{space 3} .8444063
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .2159278{col 37}{space 2} .0308455{col 48}{space 1}    7.00{col 57}{space 3}0.000{col 65}{space 4} .1554718{col 78}{space 3} .2763838
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} .1363805{col 37}{space 2} .0270287{col 48}{space 1}    5.05{col 57}{space 3}0.000{col 65}{space 4} .0834052{col 78}{space 3} .1893558
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2}-.0253731{col 37}{space 2} .0083682{col 48}{space 1}   -3.03{col 57}{space 3}0.002{col 65}{space 4}-.0417744{col 78}{space 3}-.0089718
{txt}{space 23} {c |}
{space 16}country {c |}
{space 15}Nigeria  {c |}{col 25}{res}{space 2}-.4562276{col 37}{space 2} .0365981{col 48}{space 1}  -12.47{col 57}{space 3}0.000{col 65}{space 4}-.5279586{col 78}{space 3}-.3844966
{txt}{space 14}Ethiopia  {c |}{col 25}{res}{space 2}-1.493603{col 37}{space 2}   .03346{col 48}{space 1}  -44.64{col 57}{space 3}0.000{col 65}{space 4}-1.559183{col 78}{space 3}-1.428022
{txt}{space 16}Uganda  {c |}{col 25}{res}{space 2}  -.58739{col 37}{space 2}  .037155{col 48}{space 1}  -15.81{col 57}{space 3}0.000{col 65}{space 4}-.6602125{col 78}{space 3}-.5145675
{txt}{space 14}Tanzania  {c |}{col 25}{res}{space 2} -.101613{col 37}{space 2}  .039484{col 48}{space 1}   -2.57{col 57}{space 3}0.010{col 65}{space 4}-.1790002{col 78}{space 3}-.0242258
{txt}{space 16}Malawi  {c |}{col 25}{res}{space 2} .5701751{col 37}{space 2} .0424669{col 48}{space 1}   13.43{col 57}{space 3}0.000{col 65}{space 4} .4869414{col 78}{space 3} .6534088
{txt}{space 23} {c |}
{space 19}year {c |}
{space 18}2009  {c |}{col 25}{res}{space 2} .0377544{col 37}{space 2} .0427301{col 48}{space 1}    0.88{col 57}{space 3}0.377{col 65}{space 4}-.0459951{col 78}{space 3} .1215038
{txt}{space 18}2010  {c |}{col 25}{res}{space 2} .0671174{col 37}{space 2} .0295148{col 48}{space 1}    2.27{col 57}{space 3}0.023{col 65}{space 4} .0092694{col 78}{space 3} .1249653
{txt}{space 18}2011  {c |}{col 25}{res}{space 2} .1782924{col 37}{space 2} .0370694{col 48}{space 1}    4.81{col 57}{space 3}0.000{col 65}{space 4} .1056377{col 78}{space 3} .2509471
{txt}{space 18}2012  {c |}{col 25}{res}{space 2} .0822339{col 37}{space 2}  .029415{col 48}{space 1}    2.80{col 57}{space 3}0.005{col 65}{space 4} .0245816{col 78}{space 3} .1398862
{txt}{space 18}2013  {c |}{col 25}{res}{space 2}  .054531{col 37}{space 2}  .037428{col 48}{space 1}    1.46{col 57}{space 3}0.145{col 65}{space 4}-.0188265{col 78}{space 3} .1278884
{txt}{space 18}2014  {c |}{col 25}{res}{space 2}-.0790933{col 37}{space 2} .0509241{col 48}{space 1}   -1.55{col 57}{space 3}0.120{col 65}{space 4}-.1789027{col 78}{space 3}  .020716
{txt}{space 18}2015  {c |}{col 25}{res}{space 2} .3193888{col 37}{space 2} .0345679{col 48}{space 1}    9.24{col 57}{space 3}0.000{col 65}{space 4} .2516369{col 78}{space 3} .3871407
{txt}{space 18}2018  {c |}{col 25}{res}{space 2} .6456693{col 37}{space 2} .0394445{col 48}{space 1}   16.37{col 57}{space 3}0.000{col 65}{space 4} .5683595{col 78}{space 3}  .722979
{txt}{space 23} {c |}
{space 18}_cons {c |}{col 25}{res}{space 2} 4.646407{col 37}{space 2} .0572371{col 48}{space 1}   81.18{col 57}{space 3}0.000{col 65}{space 4} 4.534224{col 78}{space 3} 4.758589
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res} .83526647
                {txt}sigma_e {c |} {res} 1.2184054
                    {txt}rho {c |} {res} .31971218{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. margins , dydx(pdd9)  at(dist_popcenter=(0 (10) 150))  level(95) saving(file1, replace)
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    61,916
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 10}0}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}10}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}20}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}30}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}40}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}50}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:7._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}60}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:8._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}70}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:9._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}80}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:10._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}90}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:11._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}100}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:12._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}110}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:13._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}120}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:14._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}130}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:15._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}140}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:16._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}150}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}pdd9         {txt}{c |}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .0606134{col 26}{space 2} .0075023{col 37}{space 1}    8.08{col 46}{space 3}0.000{col 54}{space 4} .0459092{col 67}{space 3} .0753176
{txt}{space 10}2  {c |}{col 14}{res}{space 2} .0680621{col 26}{space 2} .0070647{col 37}{space 1}    9.63{col 46}{space 3}0.000{col 54}{space 4} .0542155{col 67}{space 3} .0819086
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .0755107{col 26}{space 2}  .006769{col 37}{space 1}   11.16{col 46}{space 3}0.000{col 54}{space 4} .0622438{col 67}{space 3} .0887777
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0829594{col 26}{space 2} .0066342{col 37}{space 1}   12.50{col 46}{space 3}0.000{col 54}{space 4} .0699567{col 67}{space 3} .0959621
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .0904081{col 26}{space 2}   .00667{col 37}{space 1}   13.55{col 46}{space 3}0.000{col 54}{space 4} .0773351{col 67}{space 3} .1034811
{txt}{space 10}6  {c |}{col 14}{res}{space 2} .0978568{col 26}{space 2} .0068739{col 37}{space 1}   14.24{col 46}{space 3}0.000{col 54}{space 4} .0843842{col 67}{space 3} .1113294
{txt}{space 10}7  {c |}{col 14}{res}{space 2} .1053054{col 26}{space 2} .0072316{col 37}{space 1}   14.56{col 46}{space 3}0.000{col 54}{space 4} .0911318{col 67}{space 3} .1194791
{txt}{space 10}8  {c |}{col 14}{res}{space 2} .1127541{col 26}{space 2} .0077217{col 37}{space 1}   14.60{col 46}{space 3}0.000{col 54}{space 4} .0976198{col 67}{space 3} .1278884
{txt}{space 10}9  {c |}{col 14}{res}{space 2} .1202028{col 26}{space 2} .0083209{col 37}{space 1}   14.45{col 46}{space 3}0.000{col 54}{space 4}  .103894{col 67}{space 3} .1365115
{txt}{space 9}10  {c |}{col 14}{res}{space 2} .1276514{col 26}{space 2} .0090075{col 37}{space 1}   14.17{col 46}{space 3}0.000{col 54}{space 4}  .109997{col 67}{space 3} .1453059
{txt}{space 9}11  {c |}{col 14}{res}{space 2} .1351001{col 26}{space 2}  .009763{col 37}{space 1}   13.84{col 46}{space 3}0.000{col 54}{space 4} .1159649{col 67}{space 3} .1542353
{txt}{space 9}12  {c |}{col 14}{res}{space 2} .1425488{col 26}{space 2} .0105727{col 37}{space 1}   13.48{col 46}{space 3}0.000{col 54}{space 4} .1218267{col 67}{space 3} .1632709
{txt}{space 9}13  {c |}{col 14}{res}{space 2} .1499975{col 26}{space 2}  .011425{col 37}{space 1}   13.13{col 46}{space 3}0.000{col 54}{space 4} .1276048{col 67}{space 3} .1723901
{txt}{space 9}14  {c |}{col 14}{res}{space 2} .1574461{col 26}{space 2} .0123111{col 37}{space 1}   12.79{col 46}{space 3}0.000{col 54}{space 4} .1333167{col 67}{space 3} .1815755
{txt}{space 9}15  {c |}{col 14}{res}{space 2} .1648948{col 26}{space 2} .0132243{col 37}{space 1}   12.47{col 46}{space 3}0.000{col 54}{space 4} .1389757{col 67}{space 3} .1908139
{txt}{space 9}16  {c |}{col 14}{res}{space 2} .1723435{col 26}{space 2} .0141592{col 37}{space 1}   12.17{col 46}{space 3}0.000{col 54}{space 4}  .144592{col 67}{space 3}  .200095
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. xtreg hdd9  c.pdd9##c.dist_popcenter   $xlist  pdd9_mean  year_6 if country==3, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    13,494
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,431

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0222                                         {txt}min = {res}         1
{txt}     between = {res}0.3773                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2636                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3637.24
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:5,431} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0111538{col 37}{space 2} .0130321{col 48}{space 1}    0.86{col 57}{space 3}0.392{col 65}{space 4}-.0143886{col 78}{space 3} .0366963
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0039446{col 37}{space 2} .0006251{col 48}{space 1}   -6.31{col 57}{space 3}0.000{col 65}{space 4}-.0051697{col 78}{space 3}-.0027195
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0010726{col 37}{space 2} .0002011{col 48}{space 1}    5.33{col 57}{space 3}0.000{col 65}{space 4} .0006784{col 78}{space 3} .0014668
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2} .0480129{col 37}{space 2} .0069837{col 48}{space 1}    6.88{col 57}{space 3}0.000{col 65}{space 4} .0343252{col 78}{space 3} .0617006
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2}-.0153151{col 37}{space 2} .0538723{col 48}{space 1}   -0.28{col 57}{space 3}0.776{col 65}{space 4}-.1209028{col 78}{space 3} .0902726
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}-.0028796{col 37}{space 2} .0009423{col 48}{space 1}   -3.06{col 57}{space 3}0.002{col 65}{space 4}-.0047264{col 78}{space 3}-.0010328
{txt}{space 12}female_head {c |}{col 25}{res}{space 2}-.0146457{col 37}{space 2}  .033027{col 48}{space 1}   -0.44{col 57}{space 3}0.657{col 65}{space 4}-.0793776{col 78}{space 3} .0500861
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .3959678{col 37}{space 2} .0300212{col 48}{space 1}   13.19{col 57}{space 3}0.000{col 65}{space 4} .3371272{col 78}{space 3} .4548083
{txt}{space 15}motobike {c |}{col 25}{res}{space 2}-.1411132{col 37}{space 2} .1323959{col 48}{space 1}   -1.07{col 57}{space 3}0.286{col 65}{space 4}-.4006044{col 78}{space 3} .1183779
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .1884775{col 37}{space 2} .0369884{col 48}{space 1}    5.10{col 57}{space 3}0.000{col 65}{space 4} .1159815{col 78}{space 3} .2609734
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .1419862{col 37}{space 2} .0451709{col 48}{space 1}    3.14{col 57}{space 3}0.002{col 65}{space 4}  .053453{col 78}{space 3} .2305195
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} -.037266{col 37}{space 2} .0536996{col 48}{space 1}   -0.69{col 57}{space 3}0.488{col 65}{space 4}-.1425153{col 78}{space 3} .0679834
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2} .2112543{col 37}{space 2} .0472998{col 48}{space 1}    4.47{col 57}{space 3}0.000{col 65}{space 4} .1185484{col 78}{space 3} .3039602
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}  -.15913{col 37}{space 2} .0294416{col 48}{space 1}   -5.40{col 57}{space 3}0.000{col 65}{space 4}-.2168346{col 78}{space 3}-.1014255
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2} .0056281{col 37}{space 2} .0035341{col 48}{space 1}    1.59{col 57}{space 3}0.111{col 65}{space 4}-.0012986{col 78}{space 3} .0125548
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2} .2095101{col 37}{space 2} .0312129{col 48}{space 1}    6.71{col 57}{space 3}0.000{col 65}{space 4}  .148334{col 78}{space 3} .2706863
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2}  1.15204{col 37}{space 2} .2148533{col 48}{space 1}    5.36{col 57}{space 3}0.000{col 65}{space 4} .7309354{col 78}{space 3} 1.573145
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .5332277{col 37}{space 2} .0560909{col 48}{space 1}    9.51{col 57}{space 3}0.000{col 65}{space 4} .4232914{col 78}{space 3} .6431639
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .6155916{col 37}{space 2}  .067693{col 48}{space 1}    9.09{col 57}{space 3}0.000{col 65}{space 4} .4829158{col 78}{space 3} .7482674
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .4808063{col 37}{space 2} .0811485{col 48}{space 1}    5.93{col 57}{space 3}0.000{col 65}{space 4} .3217581{col 78}{space 3} .6398544
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} .0927379{col 37}{space 2} .0598739{col 48}{space 1}    1.55{col 57}{space 3}0.121{col 65}{space 4}-.0246128{col 78}{space 3} .2100885
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2} .0058738{col 37}{space 2} .0143358{col 48}{space 1}    0.41{col 57}{space 3}0.682{col 65}{space 4}-.0222238{col 78}{space 3} .0339715
{txt}{space 17}year_6 {c |}{col 25}{res}{space 2}-.1967094{col 37}{space 2} .0211832{col 48}{space 1}   -9.29{col 57}{space 3}0.000{col 65}{space 4}-.2382276{col 78}{space 3}-.1551911
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 3.328664{col 37}{space 2} .0734337{col 48}{space 1}   45.33{col 57}{space 3}0.000{col 65}{space 4} 3.184737{col 78}{space 3} 3.472592
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res}  .7578622
                {txt}sigma_e {c |} {res} 1.1129921
                    {txt}rho {c |} {res} .31677957{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. margins , dydx(pdd9)  at(dist_popcenter=(0 (10) 150)) level(95) saving(file2, replace)
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    13,494
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 10}0}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}10}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}20}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}30}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}40}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}50}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:7._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}60}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:8._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}70}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:9._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}80}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:10._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}90}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:11._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}100}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:12._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}110}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:13._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}120}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:14._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}130}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:15._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}140}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:16._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}150}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}pdd9         {txt}{c |}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .0111538{col 26}{space 2} .0130321{col 37}{space 1}    0.86{col 46}{space 3}0.392{col 54}{space 4}-.0143886{col 67}{space 3} .0366963
{txt}{space 10}2  {c |}{col 14}{res}{space 2} .0218799{col 26}{space 2} .0119831{col 37}{space 1}    1.83{col 46}{space 3}0.068{col 54}{space 4}-.0016065{col 67}{space 3} .0453663
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .0326059{col 26}{space 2} .0112001{col 37}{space 1}    2.91{col 46}{space 3}0.004{col 54}{space 4}  .010654{col 67}{space 3} .0545577
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0433319{col 26}{space 2} .0107416{col 37}{space 1}    4.03{col 46}{space 3}0.000{col 54}{space 4} .0222787{col 67}{space 3} .0643851
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .0540579{col 26}{space 2} .0106495{col 37}{space 1}    5.08{col 46}{space 3}0.000{col 54}{space 4} .0331852{col 67}{space 3} .0749306
{txt}{space 10}6  {c |}{col 14}{res}{space 2}  .064784{col 26}{space 2} .0109331{col 37}{space 1}    5.93{col 46}{space 3}0.000{col 54}{space 4} .0433554{col 67}{space 3} .0862125
{txt}{space 10}7  {c |}{col 14}{res}{space 2}   .07551{col 26}{space 2} .0115648{col 37}{space 1}    6.53{col 46}{space 3}0.000{col 54}{space 4} .0528433{col 67}{space 3} .0981766
{txt}{space 10}8  {c |}{col 14}{res}{space 2}  .086236{col 26}{space 2} .0124919{col 37}{space 1}    6.90{col 46}{space 3}0.000{col 54}{space 4} .0617523{col 67}{space 3} .1107197
{txt}{space 10}9  {c |}{col 14}{res}{space 2}  .096962{col 26}{space 2} .0136543{col 37}{space 1}    7.10{col 46}{space 3}0.000{col 54}{space 4}    .0702{col 67}{space 3}  .123724
{txt}{space 9}10  {c |}{col 14}{res}{space 2}  .107688{col 26}{space 2} .0149975{col 37}{space 1}    7.18{col 46}{space 3}0.000{col 54}{space 4} .0782935{col 67}{space 3} .1370825
{txt}{space 9}11  {c |}{col 14}{res}{space 2} .1184141{col 26}{space 2} .0164772{col 37}{space 1}    7.19{col 46}{space 3}0.000{col 54}{space 4} .0861193{col 67}{space 3} .1507088
{txt}{space 9}12  {c |}{col 14}{res}{space 2} .1291401{col 26}{space 2}   .01806{col 37}{space 1}    7.15{col 46}{space 3}0.000{col 54}{space 4} .0937431{col 67}{space 3}  .164537
{txt}{space 9}13  {c |}{col 14}{res}{space 2} .1398661{col 26}{space 2}  .019721{col 37}{space 1}    7.09{col 46}{space 3}0.000{col 54}{space 4} .1012136{col 67}{space 3} .1785186
{txt}{space 9}14  {c |}{col 14}{res}{space 2} .1505921{col 26}{space 2} .0214422{col 37}{space 1}    7.02{col 46}{space 3}0.000{col 54}{space 4} .1085663{col 67}{space 3}  .192618
{txt}{space 9}15  {c |}{col 14}{res}{space 2} .1613181{col 26}{space 2}   .02321{col 37}{space 1}    6.95{col 46}{space 3}0.000{col 54}{space 4} .1158274{col 67}{space 3} .2068089
{txt}{space 9}16  {c |}{col 14}{res}{space 2} .1720442{col 26}{space 2} .0250146{col 37}{space 1}    6.88{col 46}{space 3}0.000{col 54}{space 4} .1230164{col 67}{space 3} .2210719
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. xtreg hdd9  c.pdd9##c.dist_popcenter   $xlist  pdd9_mean year_3  if country==6, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     3,543
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,033

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0425                                         {txt}min = {res}         1
{txt}     between = {res}0.3367                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.2818                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1423.53
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:2,033} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0827994{col 37}{space 2} .0354003{col 48}{space 1}    2.34{col 57}{space 3}0.019{col 65}{space 4}  .013416{col 78}{space 3} .1521827
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0100045{col 37}{space 2} .0026128{col 48}{space 1}   -3.83{col 57}{space 3}0.000{col 65}{space 4}-.0151256{col 78}{space 3}-.0048835
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0021659{col 37}{space 2} .0007177{col 48}{space 1}    3.02{col 57}{space 3}0.003{col 65}{space 4} .0007593{col 78}{space 3} .0035724
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2}-.0106603{col 37}{space 2} .0132161{col 48}{space 1}   -0.81{col 57}{space 3}0.420{col 65}{space 4}-.0365633{col 78}{space 3} .0152427
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2}-.4013238{col 37}{space 2} .1202561{col 48}{space 1}   -3.34{col 57}{space 3}0.001{col 65}{space 4}-.6370214{col 78}{space 3}-.1656262
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}-.0043987{col 37}{space 2} .0018859{col 48}{space 1}   -2.33{col 57}{space 3}0.020{col 65}{space 4}-.0080951{col 78}{space 3}-.0007024
{txt}{space 12}female_head {c |}{col 25}{res}{space 2}-.1499849{col 37}{space 2} .0662149{col 48}{space 1}   -2.27{col 57}{space 3}0.024{col 65}{space 4}-.2797638{col 78}{space 3}-.0202061
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .3506916{col 37}{space 2} .0649948{col 48}{space 1}    5.40{col 57}{space 3}0.000{col 65}{space 4} .2233042{col 78}{space 3} .4780789
{txt}{space 15}motobike {c |}{col 25}{res}{space 2} .2528945{col 37}{space 2} .3840555{col 48}{space 1}    0.66{col 57}{space 3}0.510{col 65}{space 4}-.4998404{col 78}{space 3} 1.005629
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .2345152{col 37}{space 2} .0987117{col 48}{space 1}    2.38{col 57}{space 3}0.018{col 65}{space 4} .0410438{col 78}{space 3} .4279867
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .7214999{col 37}{space 2} .1823086{col 48}{space 1}    3.96{col 57}{space 3}0.000{col 65}{space 4} .3641816{col 78}{space 3} 1.078818
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .1690347{col 37}{space 2} .1087344{col 48}{space 1}    1.55{col 57}{space 3}0.120{col 65}{space 4}-.0440809{col 78}{space 3} .3821503
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2} .2481533{col 37}{space 2} .0780706{col 48}{space 1}    3.18{col 57}{space 3}0.001{col 65}{space 4} .0951377{col 78}{space 3}  .401169
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}-.1644838{col 37}{space 2} .0534949{col 48}{space 1}   -3.07{col 57}{space 3}0.002{col 65}{space 4}-.2693318{col 78}{space 3}-.0596358
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2} .0366957{col 37}{space 2}  .042247{col 48}{space 1}    0.87{col 57}{space 3}0.385{col 65}{space 4}-.0461069{col 78}{space 3} .1194984
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2}-.0140805{col 37}{space 2} .0733392{col 48}{space 1}   -0.19{col 57}{space 3}0.848{col 65}{space 4}-.1578228{col 78}{space 3} .1296618
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2}-.0894115{col 37}{space 2} .4792901{col 48}{space 1}   -0.19{col 57}{space 3}0.852{col 65}{space 4}-1.028803{col 78}{space 3} .8499799
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2}  .410412{col 37}{space 2} .1231474{col 48}{space 1}    3.33{col 57}{space 3}0.001{col 65}{space 4} .1690475{col 78}{space 3} .6517765
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .3264455{col 37}{space 2} .2066123{col 48}{space 1}    1.58{col 57}{space 3}0.114{col 65}{space 4}-.0785072{col 78}{space 3} .7313983
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .3133972{col 37}{space 2} .1331393{col 48}{space 1}    2.35{col 57}{space 3}0.019{col 65}{space 4}  .052449{col 78}{space 3} .5743453
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2}  .278429{col 37}{space 2} .1064804{col 48}{space 1}    2.61{col 57}{space 3}0.009{col 65}{space 4} .0697313{col 78}{space 3} .4871267
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2}-.0454976{col 37}{space 2} .0351965{col 48}{space 1}   -1.29{col 57}{space 3}0.196{col 65}{space 4}-.1144816{col 78}{space 3} .0234863
{txt}{space 17}year_3 {c |}{col 25}{res}{space 2} .0349143{col 37}{space 2} .0460874{col 48}{space 1}    0.76{col 57}{space 3}0.449{col 65}{space 4}-.0554153{col 78}{space 3} .1252439
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 5.685997{col 37}{space 2} .1454005{col 48}{space 1}   39.11{col 57}{space 3}0.000{col 65}{space 4} 5.401017{col 78}{space 3} 5.970977
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res} .67898512
                {txt}sigma_e {c |} {res} 1.2700233
                    {txt}rho {c |} {res} .22228798{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. margins , dydx(pdd9)  at(dist_popcenter=(0 (10) 150)) level(95) saving(file3, replace)
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     3,543
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 10}0}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}10}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}20}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}30}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}40}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}50}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:7._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}60}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:8._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}70}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:9._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}80}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:10._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}90}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:11._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}100}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:12._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}110}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:13._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}120}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:14._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}130}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:15._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}140}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:16._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}150}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}pdd9         {txt}{c |}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .0827994{col 26}{space 2} .0354003{col 37}{space 1}    2.34{col 46}{space 3}0.019{col 54}{space 4}  .013416{col 67}{space 3} .1521827
{txt}{space 10}2  {c |}{col 14}{res}{space 2} .1044579{col 26}{space 2} .0315059{col 37}{space 1}    3.32{col 46}{space 3}0.001{col 54}{space 4} .0427076{col 67}{space 3} .1662083
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .1261165{col 26}{space 2} .0288975{col 37}{space 1}    4.36{col 46}{space 3}0.000{col 54}{space 4} .0694785{col 67}{space 3} .1827545
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .1477751{col 26}{space 2} .0279377{col 37}{space 1}    5.29{col 46}{space 3}0.000{col 54}{space 4} .0930181{col 67}{space 3}  .202532
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .1694336{col 26}{space 2} .0287919{col 37}{space 1}    5.88{col 46}{space 3}0.000{col 54}{space 4} .1130025{col 67}{space 3} .2258647
{txt}{space 10}6  {c |}{col 14}{res}{space 2} .1910922{col 26}{space 2} .0313119{col 37}{space 1}    6.10{col 46}{space 3}0.000{col 54}{space 4} .1297219{col 67}{space 3} .2524625
{txt}{space 10}7  {c |}{col 14}{res}{space 2} .2127508{col 26}{space 2} .0351413{col 37}{space 1}    6.05{col 46}{space 3}0.000{col 54}{space 4} .1438752{col 67}{space 3} .2816263
{txt}{space 10}8  {c |}{col 14}{res}{space 2} .2344093{col 26}{space 2} .0399047{col 37}{space 1}    5.87{col 46}{space 3}0.000{col 54}{space 4} .1561976{col 67}{space 3} .3126211
{txt}{space 10}9  {c |}{col 14}{res}{space 2} .2560679{col 26}{space 2} .0453086{col 37}{space 1}    5.65{col 46}{space 3}0.000{col 54}{space 4} .1672647{col 67}{space 3} .3448711
{txt}{space 9}10  {c |}{col 14}{res}{space 2} .2777264{col 26}{space 2} .0511503{col 37}{space 1}    5.43{col 46}{space 3}0.000{col 54}{space 4} .1774736{col 67}{space 3} .3779793
{txt}{space 9}11  {c |}{col 14}{res}{space 2}  .299385{col 26}{space 2} .0572962{col 37}{space 1}    5.23{col 46}{space 3}0.000{col 54}{space 4} .1870866{col 67}{space 3} .4116835
{txt}{space 9}12  {c |}{col 14}{res}{space 2} .3210436{col 26}{space 2} .0636581{col 37}{space 1}    5.04{col 46}{space 3}0.000{col 54}{space 4}  .196276{col 67}{space 3} .4458112
{txt}{space 9}13  {c |}{col 14}{res}{space 2} .3427021{col 26}{space 2} .0701774{col 37}{space 1}    4.88{col 46}{space 3}0.000{col 54}{space 4}  .205157{col 67}{space 3} .4802473
{txt}{space 9}14  {c |}{col 14}{res}{space 2} .3643607{col 26}{space 2} .0768139{col 37}{space 1}    4.74{col 46}{space 3}0.000{col 54}{space 4} .2138082{col 67}{space 3} .5149132
{txt}{space 9}15  {c |}{col 14}{res}{space 2} .3860193{col 26}{space 2} .0835398{col 37}{space 1}    4.62{col 46}{space 3}0.000{col 54}{space 4} .2222842{col 67}{space 3} .5497543
{txt}{space 9}16  {c |}{col 14}{res}{space 2} .4076778{col 26}{space 2} .0903351{col 37}{space 1}    4.51{col 46}{space 3}0.000{col 54}{space 4} .2306243{col 67}{space 3} .5847313
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.  
. xtreg hdd9  c.pdd9##c.dist_popcenter    $xlist  pdd9_mean  year_4 if country==1, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,907
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,930

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0394                                         {txt}min = {res}         1
{txt}     between = {res}0.2705                                         {txt}avg = {res}       1.8
{txt}     overall = {res}0.2108                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1802.45
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:3,930} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .1382103{col 37}{space 2} .0379527{col 48}{space 1}    3.64{col 57}{space 3}0.000{col 65}{space 4} .0638244{col 78}{space 3} .2125962
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0079583{col 37}{space 2} .0007506{col 48}{space 1}  -10.60{col 57}{space 3}0.000{col 65}{space 4}-.0094294{col 78}{space 3}-.0064872
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0018045{col 37}{space 2} .0003005{col 48}{space 1}    6.00{col 57}{space 3}0.000{col 65}{space 4} .0012155{col 78}{space 3} .0023936
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2} .0156538{col 37}{space 2} .0063491{col 48}{space 1}    2.47{col 57}{space 3}0.014{col 65}{space 4} .0032098{col 78}{space 3} .0280978
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2}-.0231958{col 37}{space 2} .0969981{col 48}{space 1}   -0.24{col 57}{space 3}0.811{col 65}{space 4}-.2133087{col 78}{space 3}  .166917
{txt}{space 15}head_age {c |}{col 25}{res}{space 2} .0024271{col 37}{space 2}  .001384{col 48}{space 1}    1.75{col 57}{space 3}0.079{col 65}{space 4}-.0002855{col 78}{space 3} .0051396
{txt}{space 12}female_head {c |}{col 25}{res}{space 2} .1198442{col 37}{space 2} .0572526{col 48}{space 1}    2.09{col 57}{space 3}0.036{col 65}{space 4} .0076311{col 78}{space 3} .2320574
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .3181767{col 37}{space 2} .0438492{col 48}{space 1}    7.26{col 57}{space 3}0.000{col 65}{space 4} .2322339{col 78}{space 3} .4041196
{txt}{space 15}motobike {c |}{col 25}{res}{space 2} .2446147{col 37}{space 2} .0963321{col 48}{space 1}    2.54{col 57}{space 3}0.011{col 65}{space 4} .0558073{col 78}{space 3} .4334222
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .0976581{col 37}{space 2} .0746189{col 48}{space 1}    1.31{col 57}{space 3}0.191{col 65}{space 4}-.0485922{col 78}{space 3} .2439083
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .2136692{col 37}{space 2} .1062976{col 48}{space 1}    2.01{col 57}{space 3}0.044{col 65}{space 4} .0053297{col 78}{space 3} .4220087
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .2167708{col 37}{space 2} .0840985{col 48}{space 1}    2.58{col 57}{space 3}0.010{col 65}{space 4} .0519407{col 78}{space 3} .3816009
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2}-.1735673{col 37}{space 2} .0654069{col 48}{space 1}   -2.65{col 57}{space 3}0.008{col 65}{space 4}-.3017625{col 78}{space 3} -.045372
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}-.0863862{col 37}{space 2}  .044613{col 48}{space 1}   -1.94{col 57}{space 3}0.053{col 65}{space 4}-.1738261{col 78}{space 3} .0010537
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2}-.0014702{col 37}{space 2} .0015335{col 48}{space 1}   -0.96{col 57}{space 3}0.338{col 65}{space 4}-.0044758{col 78}{space 3} .0015354
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2} .1746848{col 37}{space 2} .2159626{col 48}{space 1}    0.81{col 57}{space 3}0.419{col 65}{space 4}-.2485941{col 78}{space 3} .5979637
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2} .1249374{col 37}{space 2}  .119406{col 48}{space 1}    1.05{col 57}{space 3}0.295{col 65}{space 4}-.1090941{col 78}{space 3} .3589688
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .2123145{col 37}{space 2} .0928687{col 48}{space 1}    2.29{col 57}{space 3}0.022{col 65}{space 4} .0302952{col 78}{space 3} .3943338
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .3758815{col 37}{space 2} .1255037{col 48}{space 1}    2.99{col 57}{space 3}0.003{col 65}{space 4} .1298989{col 78}{space 3} .6218642
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .0723677{col 37}{space 2} .1042664{col 48}{space 1}    0.69{col 57}{space 3}0.488{col 65}{space 4}-.1319907{col 78}{space 3} .2767261
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} .3152715{col 37}{space 2} .0813926{col 48}{space 1}    3.87{col 57}{space 3}0.000{col 65}{space 4} .1557449{col 78}{space 3}  .474798
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2}-.2217967{col 37}{space 2} .0394361{col 48}{space 1}   -5.62{col 57}{space 3}0.000{col 65}{space 4}-.2990899{col 78}{space 3}-.1445034
{txt}{space 17}year_4 {c |}{col 25}{res}{space 2} .2649808{col 37}{space 2} .0368617{col 48}{space 1}    7.19{col 57}{space 3}0.000{col 65}{space 4} .1927332{col 78}{space 3} .3372284
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 5.061248{col 37}{space 2} .1182241{col 48}{space 1}   42.81{col 57}{space 3}0.000{col 65}{space 4} 4.829533{col 78}{space 3} 5.292963
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res}  .5606369
                {txt}sigma_e {c |} {res} 1.3703622
                    {txt}rho {c |} {res}  .1433778{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}.  margins , dydx(pdd9)  at(dist_popcenter=(0 (10) 150)) level(95) saving(file4, replace)
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     6,907
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 10}0}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}10}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}20}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}30}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}40}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}50}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:7._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}60}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:8._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}70}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:9._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}80}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:10._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}90}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:11._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}100}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:12._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}110}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:13._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}120}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:14._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}130}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:15._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}140}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:16._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}150}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}pdd9         {txt}{c |}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .1382103{col 26}{space 2} .0379527{col 37}{space 1}    3.64{col 46}{space 3}0.000{col 54}{space 4} .0638244{col 67}{space 3} .2125962
{txt}{space 10}2  {c |}{col 14}{res}{space 2} .1562556{col 26}{space 2} .0368067{col 37}{space 1}    4.25{col 46}{space 3}0.000{col 54}{space 4} .0841159{col 67}{space 3} .2283954
{txt}{space 10}3  {c |}{col 14}{res}{space 2}  .174301{col 26}{space 2} .0358764{col 37}{space 1}    4.86{col 46}{space 3}0.000{col 54}{space 4} .1039845{col 67}{space 3} .2446175
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .1923464{col 26}{space 2} .0351791{col 37}{space 1}    5.47{col 46}{space 3}0.000{col 54}{space 4} .1233967{col 67}{space 3}  .261296
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .2103917{col 26}{space 2} .0347286{col 37}{space 1}    6.06{col 46}{space 3}0.000{col 54}{space 4} .1423249{col 67}{space 3} .2784586
{txt}{space 10}6  {c |}{col 14}{res}{space 2} .2284371{col 26}{space 2} .0345348{col 37}{space 1}    6.61{col 46}{space 3}0.000{col 54}{space 4} .1607501{col 67}{space 3} .2961241
{txt}{space 10}7  {c |}{col 14}{res}{space 2} .2464824{col 26}{space 2} .0346019{col 37}{space 1}    7.12{col 46}{space 3}0.000{col 54}{space 4}  .178664{col 67}{space 3} .3143009
{txt}{space 10}8  {c |}{col 14}{res}{space 2} .2645278{col 26}{space 2} .0349284{col 37}{space 1}    7.57{col 46}{space 3}0.000{col 54}{space 4} .1960694{col 67}{space 3} .3329862
{txt}{space 10}9  {c |}{col 14}{res}{space 2} .2825731{col 26}{space 2} .0355071{col 37}{space 1}    7.96{col 46}{space 3}0.000{col 54}{space 4} .2129804{col 67}{space 3} .3521659
{txt}{space 9}10  {c |}{col 14}{res}{space 2} .3006185{col 26}{space 2} .0363261{col 37}{space 1}    8.28{col 46}{space 3}0.000{col 54}{space 4} .2294207{col 67}{space 3} .3718163
{txt}{space 9}11  {c |}{col 14}{res}{space 2} .3186639{col 26}{space 2} .0373694{col 37}{space 1}    8.53{col 46}{space 3}0.000{col 54}{space 4} .2454211{col 67}{space 3} .3919066
{txt}{space 9}12  {c |}{col 14}{res}{space 2} .3367092{col 26}{space 2}  .038619{col 37}{space 1}    8.72{col 46}{space 3}0.000{col 54}{space 4} .2610173{col 67}{space 3} .4124011
{txt}{space 9}13  {c |}{col 14}{res}{space 2} .3547546{col 26}{space 2} .0400555{col 37}{space 1}    8.86{col 46}{space 3}0.000{col 54}{space 4} .2762472{col 67}{space 3}  .433262
{txt}{space 9}14  {c |}{col 14}{res}{space 2} .3727999{col 26}{space 2} .0416597{col 37}{space 1}    8.95{col 46}{space 3}0.000{col 54}{space 4} .2911485{col 67}{space 3} .4544514
{txt}{space 9}15  {c |}{col 14}{res}{space 2} .3908453{col 26}{space 2} .0434128{col 37}{space 1}    9.00{col 46}{space 3}0.000{col 54}{space 4} .3057578{col 67}{space 3} .4759328
{txt}{space 9}16  {c |}{col 14}{res}{space 2} .4088907{col 26}{space 2} .0452976{col 37}{space 1}    9.03{col 46}{space 3}0.000{col 54}{space 4} .3201089{col 67}{space 3} .4976724
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. xtreg hdd9  c.pdd9##c.dist_popcenter    $xlist  pdd9_mean  year_3 year_5 year_8 if country==2, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    18,590
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,222

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0390                                         {txt}min = {res}         1
{txt}     between = {res}0.3105                                         {txt}avg = {res}       2.3
{txt}     overall = {res}0.2633                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}25{txt})     =  {res}  4940.79
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:8,222} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0993216{col 37}{space 2} .0163849{col 48}{space 1}    6.06{col 57}{space 3}0.000{col 65}{space 4} .0672077{col 78}{space 3} .1314354
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0021647{col 37}{space 2} .0010417{col 48}{space 1}   -2.08{col 57}{space 3}0.038{col 65}{space 4}-.0042064{col 78}{space 3}-.0001229
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2}-.0001038{col 37}{space 2} .0004242{col 48}{space 1}   -0.24{col 57}{space 3}0.807{col 65}{space 4}-.0009352{col 78}{space 3} .0007276
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2}-.0249194{col 37}{space 2} .0044453{col 48}{space 1}   -5.61{col 57}{space 3}0.000{col 65}{space 4} -.033632{col 78}{space 3}-.0162068
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2} .1391867{col 37}{space 2} .0489418{col 48}{space 1}    2.84{col 57}{space 3}0.004{col 65}{space 4} .0432626{col 78}{space 3} .2351109
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}  .004382{col 37}{space 2} .0009019{col 48}{space 1}    4.86{col 57}{space 3}0.000{col 65}{space 4} .0026143{col 78}{space 3} .0061498
{txt}{space 12}female_head {c |}{col 25}{res}{space 2} .2167186{col 37}{space 2} .0350653{col 48}{space 1}    6.18{col 57}{space 3}0.000{col 65}{space 4} .1479918{col 78}{space 3} .2854454
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .1920503{col 37}{space 2} .0272126{col 48}{space 1}    7.06{col 57}{space 3}0.000{col 65}{space 4} .1387145{col 78}{space 3} .2453861
{txt}{space 15}motobike {c |}{col 25}{res}{space 2} .0372139{col 37}{space 2} .0383438{col 48}{space 1}    0.97{col 57}{space 3}0.332{col 65}{space 4}-.0379384{col 78}{space 3} .1123663
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .1856972{col 37}{space 2} .0383036{col 48}{space 1}    4.85{col 57}{space 3}0.000{col 65}{space 4} .1106235{col 78}{space 3} .2607708
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .0842125{col 37}{space 2} .0446496{col 48}{space 1}    1.89{col 57}{space 3}0.059{col 65}{space 4}-.0032992{col 78}{space 3} .1717242
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .2138857{col 37}{space 2} .0480874{col 48}{space 1}    4.45{col 57}{space 3}0.000{col 65}{space 4}  .119636{col 78}{space 3} .3081353
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2} .2779726{col 37}{space 2} .0390379{col 48}{space 1}    7.12{col 57}{space 3}0.000{col 65}{space 4} .2014597{col 78}{space 3} .3544855
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}-.0053992{col 37}{space 2} .0466791{col 48}{space 1}   -0.12{col 57}{space 3}0.908{col 65}{space 4}-.0968886{col 78}{space 3} .0860902
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2}-.0092658{col 37}{space 2} .0067626{col 48}{space 1}   -1.37{col 57}{space 3}0.171{col 65}{space 4}-.0225202{col 78}{space 3} .0039886
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2} .3139542{col 37}{space 2} .0599772{col 48}{space 1}    5.23{col 57}{space 3}0.000{col 65}{space 4} .1964011{col 78}{space 3} .4315074
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2}-.0533782{col 37}{space 2} .0533127{col 48}{space 1}   -1.00{col 57}{space 3}0.317{col 65}{space 4}-.1578691{col 78}{space 3} .0511128
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .8125325{col 37}{space 2}  .058538{col 48}{space 1}   13.88{col 57}{space 3}0.000{col 65}{space 4} .6978001{col 78}{space 3} .9272648
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .8372002{col 37}{space 2} .0576522{col 48}{space 1}   14.52{col 57}{space 3}0.000{col 65}{space 4}  .724204{col 78}{space 3} .9501964
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .2476453{col 37}{space 2} .0638858{col 48}{space 1}    3.88{col 57}{space 3}0.000{col 65}{space 4} .1224314{col 78}{space 3} .3728592
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} -.010171{col 37}{space 2} .0511284{col 48}{space 1}   -0.20{col 57}{space 3}0.842{col 65}{space 4}-.1103809{col 78}{space 3} .0900389
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2}-.0768763{col 37}{space 2} .0181919{col 48}{space 1}   -4.23{col 57}{space 3}0.000{col 65}{space 4}-.1125317{col 78}{space 3} -.041221
{txt}{space 17}year_3 {c |}{col 25}{res}{space 2}-.5915484{col 37}{space 2} .0311591{col 48}{space 1}  -18.98{col 57}{space 3}0.000{col 65}{space 4}-.6526191{col 78}{space 3}-.5304778
{txt}{space 17}year_5 {c |}{col 25}{res}{space 2}-.4981683{col 37}{space 2} .0312781{col 48}{space 1}  -15.93{col 57}{space 3}0.000{col 65}{space 4}-.5594722{col 78}{space 3}-.4368644
{txt}{space 17}year_8 {c |}{col 25}{res}{space 2}-.3311327{col 37}{space 2} .0308613{col 48}{space 1}  -10.73{col 57}{space 3}0.000{col 65}{space 4}-.3916197{col 78}{space 3}-.2706456
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 4.589415{col 37}{space 2} .0785149{col 48}{space 1}   58.45{col 57}{space 3}0.000{col 65}{space 4} 4.435529{col 78}{space 3} 4.743302
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res}  .8589988
                {txt}sigma_e {c |} {res} 1.2345132
                    {txt}rho {c |} {res} .32622058{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. margins , dydx(pdd9)  at(dist_popcenter=(0 (10) 150)) level(95) saving(file5, replace)
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    18,590
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 10}0}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}10}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}20}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}30}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}40}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}50}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:7._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}60}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:8._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}70}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:9._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}80}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:10._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}90}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:11._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}100}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:12._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}110}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:13._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}120}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:14._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}130}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:15._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}140}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:16._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}150}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}pdd9         {txt}{c |}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .0993216{col 26}{space 2} .0163849{col 37}{space 1}    6.06{col 46}{space 3}0.000{col 54}{space 4} .0672077{col 67}{space 3} .1314354
{txt}{space 10}2  {c |}{col 14}{res}{space 2} .0982837{col 26}{space 2} .0147516{col 37}{space 1}    6.66{col 46}{space 3}0.000{col 54}{space 4} .0693711{col 67}{space 3} .1271963
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .0972459{col 26}{space 2} .0142388{col 37}{space 1}    6.83{col 46}{space 3}0.000{col 54}{space 4} .0693384{col 67}{space 3} .1251534
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0962081{col 26}{space 2} .0149622{col 37}{space 1}    6.43{col 46}{space 3}0.000{col 54}{space 4} .0668827{col 67}{space 3} .1255334
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .0951703{col 26}{space 2} .0167625{col 37}{space 1}    5.68{col 46}{space 3}0.000{col 54}{space 4} .0623164{col 67}{space 3} .1280241
{txt}{space 10}6  {c |}{col 14}{res}{space 2} .0941324{col 26}{space 2} .0193413{col 37}{space 1}    4.87{col 46}{space 3}0.000{col 54}{space 4} .0562242{col 67}{space 3} .1320406
{txt}{space 10}7  {c |}{col 14}{res}{space 2} .0930946{col 26}{space 2} .0224316{col 37}{space 1}    4.15{col 46}{space 3}0.000{col 54}{space 4} .0491294{col 67}{space 3} .1370598
{txt}{space 10}8  {c |}{col 14}{res}{space 2} .0920568{col 26}{space 2} .0258508{col 37}{space 1}    3.56{col 46}{space 3}0.000{col 54}{space 4} .0413902{col 67}{space 3} .1427233
{txt}{space 10}9  {c |}{col 14}{res}{space 2} .0910189{col 26}{space 2} .0294845{col 37}{space 1}    3.09{col 46}{space 3}0.002{col 54}{space 4} .0332304{col 67}{space 3} .1488075
{txt}{space 9}10  {c |}{col 14}{res}{space 2} .0899811{col 26}{space 2} .0332626{col 37}{space 1}    2.71{col 46}{space 3}0.007{col 54}{space 4} .0247877{col 67}{space 3} .1551746
{txt}{space 9}11  {c |}{col 14}{res}{space 2} .0889433{col 26}{space 2}  .037141{col 37}{space 1}    2.39{col 46}{space 3}0.017{col 54}{space 4} .0161483{col 67}{space 3} .1617383
{txt}{space 9}12  {c |}{col 14}{res}{space 2} .0879055{col 26}{space 2} .0410913{col 37}{space 1}    2.14{col 46}{space 3}0.032{col 54}{space 4}  .007368{col 67}{space 3}  .168443
{txt}{space 9}13  {c |}{col 14}{res}{space 2} .0868676{col 26}{space 2} .0450947{col 37}{space 1}    1.93{col 46}{space 3}0.054{col 54}{space 4}-.0015163{col 67}{space 3} .1752516
{txt}{space 9}14  {c |}{col 14}{res}{space 2} .0858298{col 26}{space 2} .0491381{col 37}{space 1}    1.75{col 46}{space 3}0.081{col 54}{space 4}-.0104791{col 67}{space 3} .1821387
{txt}{space 9}15  {c |}{col 14}{res}{space 2}  .084792{col 26}{space 2} .0532125{col 37}{space 1}    1.59{col 46}{space 3}0.111{col 54}{space 4}-.0195025{col 67}{space 3} .1890865
{txt}{space 9}16  {c |}{col 14}{res}{space 2} .0837542{col 26}{space 2} .0573112{col 37}{space 1}    1.46{col 46}{space 3}0.144{col 54}{space 4}-.0285737{col 67}{space 3}  .196082
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. xtreg hdd9  c.pdd9##c.dist_popcenter   $xlist  pdd9_mean year_1 year_3  if country==5, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,364
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,101

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0295                                         {txt}min = {res}         1
{txt}     between = {res}0.2532                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.2147                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}24{txt})     =  {res}  2307.66
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:5,101} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0895012{col 37}{space 2} .0166281{col 48}{space 1}    5.38{col 57}{space 3}0.000{col 65}{space 4} .0569108{col 78}{space 3} .1220916
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0045376{col 37}{space 2} .0008088{col 48}{space 1}   -5.61{col 57}{space 3}0.000{col 65}{space 4}-.0061228{col 78}{space 3}-.0029525
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0004662{col 37}{space 2} .0001846{col 48}{space 1}    2.52{col 57}{space 3}0.012{col 65}{space 4} .0001043{col 78}{space 3} .0008281
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2} .0039849{col 37}{space 2} .0056103{col 48}{space 1}    0.71{col 57}{space 3}0.478{col 65}{space 4} -.007011{col 78}{space 3} .0149808
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2} .1318819{col 37}{space 2} .0710391{col 48}{space 1}    1.86{col 57}{space 3}0.063{col 65}{space 4} -.007352{col 78}{space 3} .2711159
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}-.0035287{col 37}{space 2} .0011137{col 48}{space 1}   -3.17{col 57}{space 3}0.002{col 65}{space 4}-.0057116{col 78}{space 3}-.0013458
{txt}{space 12}female_head {c |}{col 25}{res}{space 2} .0749686{col 37}{space 2} .0381213{col 48}{space 1}    1.97{col 57}{space 3}0.049{col 65}{space 4} .0002522{col 78}{space 3} .1496851
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .2903883{col 37}{space 2}  .038584{col 48}{space 1}    7.53{col 57}{space 3}0.000{col 65}{space 4} .2147651{col 78}{space 3} .3660115
{txt}{space 15}motobike {c |}{col 25}{res}{space 2}  .121971{col 37}{space 2} .0848089{col 48}{space 1}    1.44{col 57}{space 3}0.150{col 65}{space 4}-.0442514{col 78}{space 3} .2881934
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .2573053{col 37}{space 2} .0484235{col 48}{space 1}    5.31{col 57}{space 3}0.000{col 65}{space 4} .1623969{col 78}{space 3} .3522136
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .1381779{col 37}{space 2} .0834902{col 48}{space 1}    1.66{col 57}{space 3}0.098{col 65}{space 4}-.0254599{col 78}{space 3} .3018157
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .1130704{col 37}{space 2} .0392125{col 48}{space 1}    2.88{col 57}{space 3}0.004{col 65}{space 4} .0362153{col 78}{space 3} .1899255
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2}  .198002{col 37}{space 2} .0408317{col 48}{space 1}    4.85{col 57}{space 3}0.000{col 65}{space 4} .1179734{col 78}{space 3} .2780307
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}-.0123028{col 37}{space 2} .0402882{col 48}{space 1}   -0.31{col 57}{space 3}0.760{col 65}{space 4}-.0912662{col 78}{space 3} .0666607
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2} .0026366{col 37}{space 2} .0021078{col 48}{space 1}    1.25{col 57}{space 3}0.211{col 65}{space 4}-.0014946{col 78}{space 3} .0067677
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2}-.0117849{col 37}{space 2} .0384253{col 48}{space 1}   -0.31{col 57}{space 3}0.759{col 65}{space 4}-.0870971{col 78}{space 3} .0635272
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2}  .464568{col 37}{space 2} .1104582{col 48}{space 1}    4.21{col 57}{space 3}0.000{col 65}{space 4}  .248074{col 78}{space 3}  .681062
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .5846241{col 37}{space 2} .0676201{col 48}{space 1}    8.65{col 57}{space 3}0.000{col 65}{space 4} .4520911{col 78}{space 3} .7171571
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .5213169{col 37}{space 2} .0985994{col 48}{space 1}    5.29{col 57}{space 3}0.000{col 65}{space 4} .3280656{col 78}{space 3} .7145683
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .0475389{col 37}{space 2} .0575804{col 48}{space 1}    0.83{col 57}{space 3}0.409{col 65}{space 4}-.0653165{col 78}{space 3} .1603944
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} .1951055{col 37}{space 2} .0584226{col 48}{space 1}    3.34{col 57}{space 3}0.001{col 65}{space 4} .0805994{col 78}{space 3} .3096116
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2}  -.03724{col 37}{space 2} .0179113{col 48}{space 1}   -2.08{col 57}{space 3}0.038{col 65}{space 4}-.0723454{col 78}{space 3}-.0021345
{txt}{space 17}year_1 {c |}{col 25}{res}{space 2}-.0203283{col 37}{space 2} .0333094{col 48}{space 1}   -0.61{col 57}{space 3}0.542{col 65}{space 4}-.0856135{col 78}{space 3} .0449568
{txt}{space 17}year_3 {c |}{col 25}{res}{space 2} .1046363{col 37}{space 2} .0276932{col 48}{space 1}    3.78{col 57}{space 3}0.000{col 65}{space 4} .0503586{col 78}{space 3} .1589141
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 4.700038{col 37}{space 2} .0923969{col 48}{space 1}   50.87{col 57}{space 3}0.000{col 65}{space 4} 4.518943{col 78}{space 3} 4.881132
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res} .83080347
                {txt}sigma_e {c |} {res} 1.2099937
                    {txt}rho {c |} {res} .32039563{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}.  margins , dydx(pdd9)  at(dist_popcenter=(0 (10) 150)) level(95) saving(file6, replace)
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    11,364
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 10}0}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}10}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}20}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}30}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}40}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}50}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:7._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}60}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:8._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}70}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:9._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}80}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:10._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}90}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:11._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}100}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:12._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}110}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:13._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}120}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:14._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}130}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:15._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}140}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:16._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}150}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}pdd9         {txt}{c |}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .0895012{col 26}{space 2} .0166281{col 37}{space 1}    5.38{col 46}{space 3}0.000{col 54}{space 4} .0569108{col 67}{space 3} .1220916
{txt}{space 10}2  {c |}{col 14}{res}{space 2}  .094163{col 26}{space 2} .0157506{col 37}{space 1}    5.98{col 46}{space 3}0.000{col 54}{space 4} .0632924{col 67}{space 3} .1250336
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .0988249{col 26}{space 2} .0150495{col 37}{space 1}    6.57{col 46}{space 3}0.000{col 54}{space 4} .0693284{col 67}{space 3} .1283215
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .1034868{col 26}{space 2} .0145504{col 37}{space 1}    7.11{col 46}{space 3}0.000{col 54}{space 4} .0749685{col 67}{space 3} .1320051
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .1081487{col 26}{space 2} .0142744{col 37}{space 1}    7.58{col 46}{space 3}0.000{col 54}{space 4} .0801713{col 67}{space 3} .1361261
{txt}{space 10}6  {c |}{col 14}{res}{space 2} .1128106{col 26}{space 2} .0142346{col 37}{space 1}    7.93{col 46}{space 3}0.000{col 54}{space 4} .0849113{col 67}{space 3} .1407098
{txt}{space 10}7  {c |}{col 14}{res}{space 2} .1174725{col 26}{space 2} .0144328{col 37}{space 1}    8.14{col 46}{space 3}0.000{col 54}{space 4} .0891847{col 67}{space 3} .1457602
{txt}{space 10}8  {c |}{col 14}{res}{space 2} .1221343{col 26}{space 2} .0148596{col 37}{space 1}    8.22{col 46}{space 3}0.000{col 54}{space 4} .0930101{col 67}{space 3} .1512585
{txt}{space 10}9  {c |}{col 14}{res}{space 2} .1267962{col 26}{space 2}  .015496{col 37}{space 1}    8.18{col 46}{space 3}0.000{col 54}{space 4} .0964246{col 67}{space 3} .1571679
{txt}{space 9}10  {c |}{col 14}{res}{space 2} .1314581{col 26}{space 2} .0163176{col 37}{space 1}    8.06{col 46}{space 3}0.000{col 54}{space 4} .0994761{col 67}{space 3} .1634401
{txt}{space 9}11  {c |}{col 14}{res}{space 2}   .13612{col 26}{space 2} .0172981{col 37}{space 1}    7.87{col 46}{space 3}0.000{col 54}{space 4} .1022164{col 67}{space 3} .1700235
{txt}{space 9}12  {c |}{col 14}{res}{space 2} .1407819{col 26}{space 2} .0184119{col 37}{space 1}    7.65{col 46}{space 3}0.000{col 54}{space 4} .1046952{col 67}{space 3} .1768686
{txt}{space 9}13  {c |}{col 14}{res}{space 2} .1454437{col 26}{space 2} .0196365{col 37}{space 1}    7.41{col 46}{space 3}0.000{col 54}{space 4} .1069568{col 67}{space 3} .1839307
{txt}{space 9}14  {c |}{col 14}{res}{space 2} .1501056{col 26}{space 2} .0209525{col 37}{space 1}    7.16{col 46}{space 3}0.000{col 54}{space 4} .1090395{col 67}{space 3} .1911718
{txt}{space 9}15  {c |}{col 14}{res}{space 2} .1547675{col 26}{space 2} .0223437{col 37}{space 1}    6.93{col 46}{space 3}0.000{col 54}{space 4} .1109747{col 67}{space 3} .1985603
{txt}{space 9}16  {c |}{col 14}{res}{space 2} .1594294{col 26}{space 2} .0237969{col 37}{space 1}    6.70{col 46}{space 3}0.000{col 54}{space 4} .1127884{col 67}{space 3} .2060704
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. xtreg hdd9  c.pdd9##c.dist_popcenter   $xlist  pdd9_mean  year_2 year_3  if country==4, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     8,018
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,077

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0173                                         {txt}min = {res}         1
{txt}     between = {res}0.2688                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.1966                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1387.96
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:3,077} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0421998{col 37}{space 2} .0249763{col 48}{space 1}    1.69{col 57}{space 3}0.091{col 65}{space 4}-.0067528{col 78}{space 3} .0911525
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0142293{col 37}{space 2} .0023723{col 48}{space 1}   -6.00{col 57}{space 3}0.000{col 65}{space 4} -.018879{col 78}{space 3}-.0095796
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0015099{col 37}{space 2} .0006556{col 48}{space 1}    2.30{col 57}{space 3}0.021{col 65}{space 4}  .000225{col 78}{space 3} .0027948
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2}  .022239{col 37}{space 2} .0074805{col 48}{space 1}    2.97{col 57}{space 3}0.003{col 65}{space 4} .0075775{col 78}{space 3} .0369004
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2} .1137123{col 37}{space 2} .0927412{col 48}{space 1}    1.23{col 57}{space 3}0.220{col 65}{space 4}-.0680572{col 78}{space 3} .2954817
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}-.0068808{col 37}{space 2} .0013985{col 48}{space 1}   -4.92{col 57}{space 3}0.000{col 65}{space 4}-.0096218{col 78}{space 3}-.0041397
{txt}{space 12}female_head {c |}{col 25}{res}{space 2}-.0776194{col 37}{space 2}  .046654{col 48}{space 1}   -1.66{col 57}{space 3}0.096{col 65}{space 4}-.1690597{col 78}{space 3} .0138208
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .2107113{col 37}{space 2} .0468555{col 48}{space 1}    4.50{col 57}{space 3}0.000{col 65}{space 4} .1188762{col 78}{space 3} .3025464
{txt}{space 15}motobike {c |}{col 25}{res}{space 2} .0642154{col 37}{space 2} .0870374{col 48}{space 1}    0.74{col 57}{space 3}0.461{col 65}{space 4}-.1063748{col 78}{space 3} .2348056
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .1473588{col 37}{space 2}   .05616{col 48}{space 1}    2.62{col 57}{space 3}0.009{col 65}{space 4} .0372871{col 78}{space 3} .2574305
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .1293096{col 37}{space 2} .1035074{col 48}{space 1}    1.25{col 57}{space 3}0.212{col 65}{space 4}-.0735612{col 78}{space 3} .3321805
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .0169294{col 37}{space 2} .0461459{col 48}{space 1}    0.37{col 57}{space 3}0.714{col 65}{space 4} -.073515{col 78}{space 3} .1073738
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2} .2140972{col 37}{space 2} .0526316{col 48}{space 1}    4.07{col 57}{space 3}0.000{col 65}{space 4} .1109412{col 78}{space 3} .3172533
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}  .130426{col 37}{space 2} .0358739{col 48}{space 1}    3.64{col 57}{space 3}0.000{col 65}{space 4} .0601145{col 78}{space 3} .2007376
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2} .0031192{col 37}{space 2} .0013326{col 48}{space 1}    2.34{col 57}{space 3}0.019{col 65}{space 4} .0005073{col 78}{space 3} .0057311
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2}-.0058777{col 37}{space 2} .0397716{col 48}{space 1}   -0.15{col 57}{space 3}0.883{col 65}{space 4}-.0838287{col 78}{space 3} .0720732
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2} .3530031{col 37}{space 2} .1278794{col 48}{space 1}    2.76{col 57}{space 3}0.006{col 65}{space 4} .1023642{col 78}{space 3} .6036421
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .5201955{col 37}{space 2} .0813011{col 48}{space 1}    6.40{col 57}{space 3}0.000{col 65}{space 4} .3608483{col 78}{space 3} .6795428
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .7766215{col 37}{space 2} .1333311{col 48}{space 1}    5.82{col 57}{space 3}0.000{col 65}{space 4} .5152972{col 78}{space 3} 1.037946
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .0393298{col 37}{space 2} .0744002{col 48}{space 1}    0.53{col 57}{space 3}0.597{col 65}{space 4} -.106492{col 78}{space 3} .1851515
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} .1865708{col 37}{space 2} .0743971{col 48}{space 1}    2.51{col 57}{space 3}0.012{col 65}{space 4}  .040755{col 78}{space 3} .3323865
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2} .0104978{col 37}{space 2} .0255541{col 48}{space 1}    0.41{col 57}{space 3}0.681{col 65}{space 4}-.0395874{col 78}{space 3} .0605829
{txt}{space 17}year_2 {c |}{col 25}{res}{space 2} -.216024{col 37}{space 2} .0352212{col 48}{space 1}   -6.13{col 57}{space 3}0.000{col 65}{space 4}-.2850562{col 78}{space 3}-.1469918
{txt}{space 17}year_3 {c |}{col 25}{res}{space 2}-.1354934{col 37}{space 2}  .036243{col 48}{space 1}   -3.74{col 57}{space 3}0.000{col 65}{space 4}-.2065283{col 78}{space 3}-.0644584
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 4.672004{col 37}{space 2} .1246315{col 48}{space 1}   37.49{col 57}{space 3}0.000{col 65}{space 4}  4.42773{col 78}{space 3} 4.916277
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res} .89217853
                {txt}sigma_e {c |} {res} 1.2274622
                    {txt}rho {c |} {res} .34568167{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}.  margins , dydx(pdd9)  at(dist_popcenter=(0 (10) 150)) level(95) saving(file7, replace)
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     8,018
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 10}0}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}10}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}20}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}30}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}40}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}50}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:7._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}60}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:8._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}70}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:9._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}80}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:10._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 9}90}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:11._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}100}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:12._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}110}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:13._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}120}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:14._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}130}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:15._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}140}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:16._at}:{space 1}{res:{txt:dist_popce~r}{space 4}{txt:=} {space 8}150}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}pdd9         {txt}{c |}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .0421998{col 26}{space 2} .0249763{col 37}{space 1}    1.69{col 46}{space 3}0.091{col 54}{space 4}-.0067528{col 67}{space 3} .0911525
{txt}{space 10}2  {c |}{col 14}{res}{space 2}  .057299{col 26}{space 2} .0214254{col 37}{space 1}    2.67{col 46}{space 3}0.007{col 54}{space 4}  .015306{col 67}{space 3} .0992921
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .0723982{col 26}{space 2} .0194998{col 37}{space 1}    3.71{col 46}{space 3}0.000{col 54}{space 4} .0341794{col 67}{space 3} .1106171
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0874974{col 26}{space 2} .0196823{col 37}{space 1}    4.45{col 46}{space 3}0.000{col 54}{space 4} .0489209{col 67}{space 3}  .126074
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .1025966{col 26}{space 2} .0219204{col 37}{space 1}    4.68{col 46}{space 3}0.000{col 54}{space 4} .0596335{col 67}{space 3} .1455598
{txt}{space 10}6  {c |}{col 14}{res}{space 2} .1176958{col 26}{space 2} .0256821{col 37}{space 1}    4.58{col 46}{space 3}0.000{col 54}{space 4} .0673598{col 67}{space 3} .1680319
{txt}{space 10}7  {c |}{col 14}{res}{space 2}  .132795{col 26}{space 2} .0304072{col 37}{space 1}    4.37{col 46}{space 3}0.000{col 54}{space 4}  .073198{col 67}{space 3} .1923921
{txt}{space 10}8  {c |}{col 14}{res}{space 2} .1478942{col 26}{space 2} .0357153{col 37}{space 1}    4.14{col 46}{space 3}0.000{col 54}{space 4} .0778934{col 67}{space 3}  .217895
{txt}{space 10}9  {c |}{col 14}{res}{space 2} .1629934{col 26}{space 2} .0413827{col 37}{space 1}    3.94{col 46}{space 3}0.000{col 54}{space 4} .0818848{col 67}{space 3} .2441021
{txt}{space 9}10  {c |}{col 14}{res}{space 2} .1780926{col 26}{space 2} .0472804{col 37}{space 1}    3.77{col 46}{space 3}0.000{col 54}{space 4} .0854248{col 67}{space 3} .2707605
{txt}{space 9}11  {c |}{col 14}{res}{space 2} .1931918{col 26}{space 2}  .053332{col 37}{space 1}    3.62{col 46}{space 3}0.000{col 54}{space 4} .0886631{col 67}{space 3} .2977206
{txt}{space 9}12  {c |}{col 14}{res}{space 2}  .208291{col 26}{space 2} .0594905{col 37}{space 1}    3.50{col 46}{space 3}0.000{col 54}{space 4} .0916918{col 67}{space 3} .3248903
{txt}{space 9}13  {c |}{col 14}{res}{space 2} .2233902{col 26}{space 2}  .065726{col 37}{space 1}    3.40{col 46}{space 3}0.001{col 54}{space 4} .0945697{col 67}{space 3} .3522108
{txt}{space 9}14  {c |}{col 14}{res}{space 2} .2384894{col 26}{space 2} .0720183{col 37}{space 1}    3.31{col 46}{space 3}0.001{col 54}{space 4} .0973361{col 67}{space 3} .3796428
{txt}{space 9}15  {c |}{col 14}{res}{space 2} .2535886{col 26}{space 2} .0783539{col 37}{space 1}    3.24{col 46}{space 3}0.001{col 54}{space 4} .1000177{col 67}{space 3} .4071595
{txt}{space 9}16  {c |}{col 14}{res}{space 2} .2686878{col 26}{space 2} .0847231{col 37}{space 1}    3.17{col 46}{space 3}0.002{col 54}{space 4} .1026337{col 67}{space 3}  .434742
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. combomarginsplot  file1 file2 file3 file4 file5  file6 file7, labels( "All countries" "Ethiopia" "Malawi"  "Niger" "Nigeria"  "Tanzania"  "Uganda", size(small) )     ci1opt(color(%5))  ci2opt(color(%5)) ci3opt(color(%5)) ci4opt(color(%5)) ci5opt(color(%5)) ci6opt(color(%5)) ci7opt(color(%5)) title("Impact of production diversity on household dietary diversity by proximity to a center area", size(small))   xlabel(, labsize(small))   xtitle("Distance (km)", size(small)) ytitle("HDDS", size(small)) legend(size(small) rows(2) nobox region(lstyle(none)))  recastci(rcap) file1opts(msymbol(c) mlcolor(navy) mfcolor(navy))  file2opts(msymbol(X) mlcolor(orange) mfcolor(white))  file3opts(msymbol(t) mlcolor(lavender) mfcolor(white))  file4opts(msymbol(d) mlcolor(gold) mfcolor(white)) file5opts(msymbol(s) mlcolor(green) mfcolor(white)) file6opts(msymbol(|) mlcolor(red) mfcolor(white)) file7opts(msymbol(c) mlcolor(cranberry) mfcolor(white)) plotopts( lpattern(shortdash) lcolor(%10))
{res}
{text}{p 2 6 2}Variables that uniquely identify margins: dist_popcenter _filenumber{p_end}
{p 0 4 2}
{txt}(note:  named style
c not found in class
symbol,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
c not found in class
symbol,  default attributes used)
{p_end}
{res}{txt}
{com}.   graph save "Figure_3a_Distance_Pop.gph", replace
{res}{txt}(file Figure_3a_Distance_Pop.gph saved)

{com}. restore
{txt}
{com}. 
. 
. 
. 
. ********************************************************************************
. *                          Figure 3c                                           *         
. ********************************************************************************
. preserve
{txt}
{com}. eststo clear
{txt}
{com}. drop if hdd9_own==.|hdd9_purchase==.
{txt}(7,192 observations deleted)

{com}. drop pdd9_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. egen pdd9_mean=mean(pdd9), by(HHID_panel)
{txt}
{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. *whole
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean i.country i.year  , cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    82,550
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    34,744

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0782                                         {txt}min = {res}         1
{txt}     between = {res}0.6105                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.5185                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 70956.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:34,744} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2289411{col 30}{space 2} .0053368{col 41}{space 1}   42.90{col 50}{space 3}0.000{col 58}{space 4} .2184811{col 71}{space 3}  .239401
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0199893{col 30}{space 2} .0018284{col 41}{space 1}   10.93{col 50}{space 3}0.000{col 58}{space 4} .0164058{col 71}{space 3} .0235729
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0316314{col 30}{space 2} .0184609{col 41}{space 1}   -1.71{col 50}{space 3}0.087{col 58}{space 4}-.0678141{col 71}{space 3} .0045512
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0018132{col 30}{space 2} .0003194{col 41}{space 1}    5.68{col 50}{space 3}0.000{col 58}{space 4} .0011872{col 71}{space 3} .0024393
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0368507{col 30}{space 2} .0112429{col 41}{space 1}   -3.28{col 50}{space 3}0.001{col 58}{space 4}-.0588864{col 71}{space 3} -.014815
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0820646{col 30}{space 2} .0108273{col 41}{space 1}    7.58{col 50}{space 3}0.000{col 58}{space 4} .0608435{col 71}{space 3} .1032857
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .000432{col 30}{space 2} .0202187{col 41}{space 1}    0.02{col 50}{space 3}0.983{col 58}{space 4} -.039196{col 71}{space 3} .0400599
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0151645{col 30}{space 2} .0147642{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.0137728{col 71}{space 3} .0441018
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0292366{col 30}{space 2} .0175851{col 41}{space 1}   -1.66{col 50}{space 3}0.096{col 58}{space 4}-.0637028{col 71}{space 3} .0052296
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0711801{col 30}{space 2} .0140919{col 41}{space 1}   -5.05{col 50}{space 3}0.000{col 58}{space 4}-.0987997{col 71}{space 3}-.0435606
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0074432{col 30}{space 2} .0139657{col 41}{space 1}    0.53{col 50}{space 3}0.594{col 58}{space 4}-.0199292{col 71}{space 3} .0348156
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0130409{col 30}{space 2}  .011313{col 41}{space 1}   -1.15{col 50}{space 3}0.249{col 58}{space 4}-.0352139{col 71}{space 3} .0091322
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0053113{col 30}{space 2} .0010791{col 41}{space 1}    4.92{col 50}{space 3}0.000{col 58}{space 4} .0031964{col 71}{space 3} .0074263
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1687443{col 30}{space 2} .0142739{col 41}{space 1}   11.82{col 50}{space 3}0.000{col 58}{space 4} .1407679{col 71}{space 3} .1967207
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0960305{col 30}{space 2} .0262241{col 41}{space 1}    3.66{col 50}{space 3}0.000{col 58}{space 4} .0446321{col 71}{space 3} .1474289
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0165833{col 30}{space 2} .0206869{col 41}{space 1}    0.80{col 50}{space 3}0.423{col 58}{space 4}-.0239622{col 71}{space 3} .0571288
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1111915{col 30}{space 2} .0221938{col 41}{space 1}   -5.01{col 50}{space 3}0.000{col 58}{space 4}-.1546905{col 71}{space 3}-.0676924
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1531674{col 30}{space 2} .0192232{col 41}{space 1}   -7.97{col 50}{space 3}0.000{col 58}{space 4}-.1908442{col 71}{space 3}-.1154905
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2531462{col 30}{space 2}   .01811{col 41}{space 1}  -13.98{col 50}{space 3}0.000{col 58}{space 4}-.2886411{col 71}{space 3}-.2176514
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2998333{col 30}{space 2} .0063445{col 41}{space 1}   47.26{col 50}{space 3}0.000{col 58}{space 4} .2873982{col 71}{space 3} .3122683
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} .3496918{col 30}{space 2} .0198542{col 41}{space 1}   17.61{col 50}{space 3}0.000{col 58}{space 4} .3107782{col 71}{space 3} .3886054
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.1162756{col 30}{space 2} .0208903{col 41}{space 1}   -5.57{col 50}{space 3}0.000{col 58}{space 4}-.1572199{col 71}{space 3}-.0753314
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} .9876464{col 30}{space 2} .0217937{col 41}{space 1}   45.32{col 50}{space 3}0.000{col 58}{space 4} .9449316{col 71}{space 3} 1.030361
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .5374965{col 30}{space 2} .0187986{col 41}{space 1}   28.59{col 50}{space 3}0.000{col 58}{space 4} .5006519{col 71}{space 3} .5743411
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .6413401{col 30}{space 2} .0256115{col 41}{space 1}   25.04{col 50}{space 3}0.000{col 58}{space 4} .5911425{col 71}{space 3} .6915376
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2} -.243842{col 30}{space 2} .0324283{col 41}{space 1}   -7.52{col 50}{space 3}0.000{col 58}{space 4}-.3074004{col 71}{space 3}-.1802837
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0857712{col 30}{space 2} .0227618{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.1303835{col 71}{space 3}-.0411588
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}   .12744{col 30}{space 2} .0258958{col 41}{space 1}    4.92{col 50}{space 3}0.000{col 58}{space 4} .0766852{col 71}{space 3} .1781948
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0123648{col 30}{space 2} .0227804{col 41}{space 1}    0.54{col 50}{space 3}0.587{col 58}{space 4}-.0322839{col 71}{space 3} .0570135
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0815978{col 30}{space 2} .0267822{col 41}{space 1}    3.05{col 50}{space 3}0.002{col 58}{space 4} .0291058{col 71}{space 3} .1340899
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1557594{col 30}{space 2} .0246973{col 41}{space 1}   -6.31{col 50}{space 3}0.000{col 58}{space 4}-.2041652{col 71}{space 3}-.1073537
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0708934{col 30}{space 2} .0249503{col 41}{space 1}    2.84{col 50}{space 3}0.004{col 58}{space 4} .0219917{col 71}{space 3}  .119795
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.3353845{col 30}{space 2} .0348631{col 41}{space 1}   -9.62{col 50}{space 3}0.000{col 58}{space 4}-.4037149{col 71}{space 3}-.2670541
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .2965881{col 30}{space 2} .0269857{col 41}{space 1}   10.99{col 50}{space 3}0.000{col 58}{space 4} .2436972{col 71}{space 3}  .349479
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.1455278{col 30}{space 2} .0277582{col 41}{space 1}   -5.24{col 50}{space 3}0.000{col 58}{space 4}-.1999329{col 71}{space 3}-.0911227
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}-.1881102{col 30}{space 2} .0339461{col 41}{space 1}   -5.54{col 50}{space 3}0.000{col 58}{space 4}-.2546432{col 71}{space 3}-.1215771
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .41007338
         {txt}sigma_e {c |} {res} 1.0171168
             {txt}rho {c |} {res} .13982041{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean i.country i.year  , cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    82,550
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    34,744

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0283                                         {txt}min = {res}         1
{txt}     between = {res}0.4949                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.4217                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 45211.41
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:34,744} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0039823{col 30}{space 2} .0063817{col 41}{space 1}    0.62{col 50}{space 3}0.533{col 58}{space 4}-.0085256{col 71}{space 3} .0164901
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0011206{col 30}{space 2} .0027949{col 41}{space 1}    0.40{col 50}{space 3}0.688{col 58}{space 4}-.0043574{col 71}{space 3} .0065986
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0361638{col 30}{space 2} .0290758{col 41}{space 1}   -1.24{col 50}{space 3}0.214{col 58}{space 4}-.0931512{col 71}{space 3} .0208236
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0038962{col 30}{space 2}  .000509{col 41}{space 1}   -7.65{col 50}{space 3}0.000{col 58}{space 4}-.0048939{col 71}{space 3}-.0028985
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0167018{col 30}{space 2} .0176895{col 41}{space 1}    0.94{col 50}{space 3}0.345{col 58}{space 4} -.017969{col 71}{space 3} .0513725
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .295018{col 30}{space 2} .0157294{col 41}{space 1}   18.76{col 50}{space 3}0.000{col 58}{space 4}  .264189{col 71}{space 3} .3258471
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1239685{col 30}{space 2} .0289665{col 41}{space 1}    4.28{col 50}{space 3}0.000{col 58}{space 4} .0671952{col 71}{space 3} .1807417
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2649609{col 30}{space 2} .0200931{col 41}{space 1}   13.19{col 50}{space 3}0.000{col 58}{space 4} .2255791{col 71}{space 3} .3043428
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2663456{col 30}{space 2} .0240881{col 41}{space 1}   11.06{col 50}{space 3}0.000{col 58}{space 4} .2191339{col 71}{space 3} .3135574
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2150796{col 30}{space 2} .0193795{col 41}{space 1}   11.10{col 50}{space 3}0.000{col 58}{space 4} .1770964{col 71}{space 3} .2530628
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2902488{col 30}{space 2} .0187777{col 41}{space 1}   15.46{col 50}{space 3}0.000{col 58}{space 4} .2534452{col 71}{space 3} .3270525
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0495975{col 30}{space 2} .0152594{col 41}{space 1}   -3.25{col 50}{space 3}0.001{col 58}{space 4}-.0795054{col 71}{space 3}-.0196897
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0011953{col 30}{space 2} .0012324{col 41}{space 1}   -0.97{col 50}{space 3}0.332{col 58}{space 4}-.0036108{col 71}{space 3} .0012202
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0367639{col 30}{space 2} .0184072{col 41}{space 1}   -2.00{col 50}{space 3}0.046{col 58}{space 4}-.0728414{col 71}{space 3}-.0006865
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0411037{col 30}{space 2} .0398198{col 41}{space 1}    1.03{col 50}{space 3}0.302{col 58}{space 4}-.0369417{col 71}{space 3} .1191492
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6645476{col 30}{space 2} .0300037{col 41}{space 1}   22.15{col 50}{space 3}0.000{col 58}{space 4} .6057413{col 71}{space 3} .7233538
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .814626{col 30}{space 2} .0328596{col 41}{space 1}   24.79{col 50}{space 3}0.000{col 58}{space 4} .7502223{col 71}{space 3} .8790297
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3505039{col 30}{space 2} .0293255{col 41}{space 1}   11.95{col 50}{space 3}0.000{col 58}{space 4}  .293027{col 71}{space 3} .4079808
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4580629{col 30}{space 2} .0267057{col 41}{space 1}   17.15{col 50}{space 3}0.000{col 58}{space 4} .4057207{col 71}{space 3} .5104052
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} -.248023{col 30}{space 2} .0082945{col 41}{space 1}  -29.90{col 50}{space 3}0.000{col 58}{space 4}  -.26428{col 71}{space 3} -.231766
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.7083755{col 30}{space 2} .0336388{col 41}{space 1}  -21.06{col 50}{space 3}0.000{col 58}{space 4}-.7743062{col 71}{space 3}-.6424447
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.905325{col 30}{space 2} .0341543{col 41}{space 1}  -55.79{col 50}{space 3}0.000{col 58}{space 4}-1.972266{col 71}{space 3}-1.838384
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-1.344389{col 30}{space 2} .0346999{col 41}{space 1}  -38.74{col 50}{space 3}0.000{col 58}{space 4}-1.412399{col 71}{space 3}-1.276378
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.8451787{col 30}{space 2} .0329501{col 41}{space 1}  -25.65{col 50}{space 3}0.000{col 58}{space 4}-.9097597{col 71}{space 3}-.7805976
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} -.161006{col 30}{space 2} .0412185{col 41}{space 1}   -3.91{col 50}{space 3}0.000{col 58}{space 4}-.2417927{col 71}{space 3}-.0802192
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1644622{col 30}{space 2} .0431813{col 41}{space 1}   -3.81{col 50}{space 3}0.000{col 58}{space 4}-.2490959{col 71}{space 3}-.0798285
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0023028{col 30}{space 2} .0306318{col 41}{space 1}   -0.08{col 50}{space 3}0.940{col 58}{space 4}-.0623401{col 71}{space 3} .0577346
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0654856{col 30}{space 2} .0359749{col 41}{space 1}   -1.82{col 50}{space 3}0.069{col 58}{space 4} -.135995{col 71}{space 3} .0050239
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} -.036667{col 30}{space 2} .0309902{col 41}{space 1}   -1.18{col 50}{space 3}0.237{col 58}{space 4}-.0974067{col 71}{space 3} .0240727
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1102496{col 30}{space 2} .0363537{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .0389977{col 71}{space 3} .1815016
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0319152{col 30}{space 2} .0360631{col 41}{space 1}   -0.88{col 50}{space 3}0.376{col 58}{space 4}-.1025977{col 71}{space 3} .0387672
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2154467{col 30}{space 2} .0345638{col 41}{space 1}    6.23{col 50}{space 3}0.000{col 58}{space 4} .1477029{col 71}{space 3} .2831905
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} .1338088{col 30}{space 2} .0488965{col 41}{space 1}    2.74{col 50}{space 3}0.006{col 58}{space 4} .0379733{col 71}{space 3} .2296442
{txt}{space 11}2018  {c |}{col 18}{res}{space 2}  .274568{col 30}{space 2}  .037372{col 41}{space 1}    7.35{col 50}{space 3}0.000{col 58}{space 4} .2013201{col 71}{space 3} .3478158
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .1881666{col 30}{space 2} .0380428{col 41}{space 1}    4.95{col 50}{space 3}0.000{col 58}{space 4} .1136041{col 71}{space 3} .2627291
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.461853{col 30}{space 2} .0532222{col 41}{space 1}   83.83{col 50}{space 3}0.000{col 58}{space 4}  4.35754{col 71}{space 3} 4.566167
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .98471562
         {txt}sigma_e {c |} {res} 1.3909744
             {txt}rho {c |} {res} .33385206{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. 
. rename  pdd9       pdd9_1
{res}{txt}
{com}. *Ethiopia
. xtreg hdd9_own  pdd9_1    $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,583
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,088

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0275                                         {txt}min = {res}         1
{txt}     between = {res}0.6382                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.5168                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res} 10582.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,088} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_1 {c |}{col 18}{res}{space 2} .0725307{col 30}{space 2} .0109034{col 41}{space 1}    6.65{col 50}{space 3}0.000{col 58}{space 4} .0511604{col 71}{space 3}  .093901
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .029883{col 30}{space 2} .0054403{col 41}{space 1}    5.49{col 50}{space 3}0.000{col 58}{space 4} .0192203{col 71}{space 3} .0405457
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0198742{col 30}{space 2} .0403712{col 41}{space 1}   -0.49{col 50}{space 3}0.623{col 58}{space 4}-.0990002{col 71}{space 3} .0592519
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0019179{col 30}{space 2} .0006944{col 41}{space 1}    2.76{col 50}{space 3}0.006{col 58}{space 4}  .000557{col 71}{space 3} .0032788
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0661727{col 30}{space 2} .0230801{col 41}{space 1}   -2.87{col 50}{space 3}0.004{col 58}{space 4}-.1114089{col 71}{space 3}-.0209365
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0925665{col 30}{space 2} .0240914{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0453482{col 71}{space 3} .1397848
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1470962{col 30}{space 2} .1247508{col 41}{space 1}   -1.18{col 50}{space 3}0.238{col 58}{space 4}-.3916034{col 71}{space 3}  .097411
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .024182{col 30}{space 2} .0349653{col 41}{space 1}    0.69{col 50}{space 3}0.489{col 58}{space 4}-.0443487{col 71}{space 3} .0927127
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1526929{col 30}{space 2} .0409561{col 41}{space 1}   -3.73{col 50}{space 3}0.000{col 58}{space 4}-.2329653{col 71}{space 3}-.0724204
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0158386{col 30}{space 2} .0339591{col 41}{space 1}   -0.47{col 50}{space 3}0.641{col 58}{space 4}-.0823971{col 71}{space 3}   .05072
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0222789{col 30}{space 2} .0405573{col 41}{space 1}   -0.55{col 50}{space 3}0.583{col 58}{space 4}-.1017698{col 71}{space 3} .0572121
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1410461{col 30}{space 2} .0261434{col 41}{space 1}   -5.40{col 50}{space 3}0.000{col 58}{space 4}-.1922862{col 71}{space 3} -.089806
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0195358{col 30}{space 2}  .006519{col 41}{space 1}    3.00{col 50}{space 3}0.003{col 58}{space 4} .0067588{col 71}{space 3} .0323129
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0194398{col 30}{space 2} .0276761{col 41}{space 1}   -0.70{col 50}{space 3}0.482{col 58}{space 4}-.0736839{col 71}{space 3} .0348042
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1873364{col 30}{space 2}  .171457{col 41}{space 1}    1.09{col 50}{space 3}0.275{col 58}{space 4}-.1487131{col 71}{space 3} .5233859
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0795805{col 30}{space 2} .0475415{col 41}{space 1}   -1.67{col 50}{space 3}0.094{col 58}{space 4}-.1727601{col 71}{space 3} .0135992
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2213507{col 30}{space 2} .0540766{col 41}{space 1}   -4.09{col 50}{space 3}0.000{col 58}{space 4}-.3273389{col 71}{space 3}-.1153624
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2066598{col 30}{space 2} .0461313{col 41}{space 1}   -4.48{col 50}{space 3}0.000{col 58}{space 4}-.2970755{col 71}{space 3} -.116244
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1966504{col 30}{space 2} .0484207{col 41}{space 1}   -4.06{col 50}{space 3}0.000{col 58}{space 4}-.2915533{col 71}{space 3}-.1017475
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2792311{col 30}{space 2} .0130262{col 41}{space 1}   21.44{col 50}{space 3}0.000{col 58}{space 4} .2537002{col 71}{space 3} .3047621
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1285239{col 30}{space 2}  .016266{col 41}{space 1}   -7.90{col 50}{space 3}0.000{col 58}{space 4}-.1604046{col 71}{space 3}-.0966432
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .4724241{col 30}{space 2} .0491895{col 41}{space 1}    9.60{col 50}{space 3}0.000{col 58}{space 4} .3760146{col 71}{space 3} .5688337
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .42273203
         {txt}sigma_e {c |} {res} .80682908
             {txt}rho {c |} {res} .21538826{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. xtreg hdd9_purchase  pdd9_1    $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,583
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,088

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0329                                         {txt}min = {res}         1
{txt}     between = {res}0.5607                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.4766                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  7204.91
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,088} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_1 {c |}{col 18}{res}{space 2} .0288698{col 30}{space 2} .0130466{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4}  .003299{col 71}{space 3} .0544406
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0343251{col 30}{space 2} .0083259{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4} .0180067{col 71}{space 3} .0506435
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0074607{col 30}{space 2} .0660029{col 41}{space 1}   -0.11{col 50}{space 3}0.910{col 58}{space 4}-.1368239{col 71}{space 3} .1219026
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0049179{col 30}{space 2} .0011278{col 41}{space 1}   -4.36{col 50}{space 3}0.000{col 58}{space 4}-.0071285{col 71}{space 3}-.0027074
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0080696{col 30}{space 2} .0394135{col 41}{space 1}   -0.20{col 50}{space 3}0.838{col 58}{space 4}-.0853187{col 71}{space 3} .0691794
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3376892{col 30}{space 2} .0357286{col 41}{space 1}    9.45{col 50}{space 3}0.000{col 58}{space 4} .2676624{col 71}{space 3}  .407716
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .052808{col 30}{space 2} .1716289{col 41}{space 1}    0.31{col 50}{space 3}0.758{col 58}{space 4}-.2835784{col 71}{space 3} .3891944
{txt}{space 11}phone {c |}{col 18}{res}{space 2}   .20484{col 30}{space 2} .0445754{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .1174738{col 71}{space 3} .2922061
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4047418{col 30}{space 2} .0542589{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .2983964{col 71}{space 3} .5110873
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0617334{col 30}{space 2} .0645079{col 41}{space 1}   -0.96{col 50}{space 3}0.339{col 58}{space 4}-.1881665{col 71}{space 3} .0646998
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3012055{col 30}{space 2} .0608703{col 41}{space 1}    4.95{col 50}{space 3}0.000{col 58}{space 4} .1819018{col 71}{space 3} .4205091
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1294374{col 30}{space 2}  .035026{col 41}{space 1}   -3.70{col 50}{space 3}0.000{col 58}{space 4} -.198087{col 71}{space 3}-.0607878
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.012986{col 30}{space 2} .0057751{col 41}{space 1}   -2.25{col 50}{space 3}0.025{col 58}{space 4} -.024305{col 71}{space 3} -.001667
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2340699{col 30}{space 2} .0371021{col 41}{space 1}    6.31{col 50}{space 3}0.000{col 58}{space 4} .1613511{col 71}{space 3} .3067888
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .6972608{col 30}{space 2} .2569264{col 41}{space 1}    2.71{col 50}{space 3}0.007{col 58}{space 4} .1936943{col 71}{space 3} 1.200827
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6672631{col 30}{space 2} .0674285{col 41}{space 1}    9.90{col 50}{space 3}0.000{col 58}{space 4} .5351056{col 71}{space 3} .7994206
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .859345{col 30}{space 2} .0795023{col 41}{space 1}   10.81{col 50}{space 3}0.000{col 58}{space 4} .7035233{col 71}{space 3} 1.015167
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .7876162{col 30}{space 2} .0941898{col 41}{space 1}    8.36{col 50}{space 3}0.000{col 58}{space 4} .6030075{col 71}{space 3} .9722249
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3486485{col 30}{space 2} .0750383{col 41}{space 1}    4.65{col 50}{space 3}0.000{col 58}{space 4} .2015761{col 71}{space 3} .4957209
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2021654{col 30}{space 2} .0172347{col 41}{space 1}  -11.73{col 50}{space 3}0.000{col 58}{space 4}-.2359448{col 71}{space 3} -.168386
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.2297235{col 30}{space 2} .0245453{col 41}{space 1}   -9.36{col 50}{space 3}0.000{col 58}{space 4}-.2778314{col 71}{space 3}-.1816157
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.304581{col 30}{space 2} .0849323{col 41}{space 1}   27.13{col 50}{space 3}0.000{col 58}{space 4} 2.138117{col 71}{space 3} 2.471045
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .92124527
         {txt}sigma_e {c |} {res} 1.1082993
             {txt}rho {c |} {res}  .4086108{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. rename  pdd9_1      pdd9_2
{res}{txt}
{com}. *Malawi
. xtreg hdd9_own  pdd9_2    $xlist  pdd9_mean $year_MALAWI if country==6, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,155
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,447

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1662                                         {txt}min = {res}         1
{txt}     between = {res}0.5607                                         {txt}avg = {res}       2.7
{txt}     overall = {res}0.4503                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  7010.28
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_2 {c |}{col 18}{res}{space 2} .3173126{col 30}{space 2} .0133082{col 41}{space 1}   23.84{col 50}{space 3}0.000{col 58}{space 4}  .291229{col 71}{space 3} .3433962
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0027509{col 30}{space 2} .0071995{col 41}{space 1}   -0.38{col 50}{space 3}0.702{col 58}{space 4}-.0168617{col 71}{space 3} .0113599
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0287026{col 30}{space 2} .0572435{col 41}{space 1}   -0.50{col 50}{space 3}0.616{col 58}{space 4}-.1408979{col 71}{space 3} .0834926
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0029858{col 30}{space 2} .0010369{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0009535{col 71}{space 3} .0050181
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} -.067816{col 30}{space 2} .0332682{col 41}{space 1}   -2.04{col 50}{space 3}0.042{col 58}{space 4}-.1330205{col 71}{space 3}-.0026116
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0585542{col 30}{space 2} .0359559{col 41}{space 1}    1.63{col 50}{space 3}0.103{col 58}{space 4}-.0119181{col 71}{space 3} .1290266
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2289414{col 30}{space 2} .1251567{col 41}{space 1}    1.83{col 50}{space 3}0.067{col 58}{space 4}-.0163612{col 71}{space 3}  .474244
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .008772{col 30}{space 2} .0419425{col 41}{space 1}    0.21{col 50}{space 3}0.834{col 58}{space 4}-.0734339{col 71}{space 3} .0909779
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0624507{col 30}{space 2} .0632369{col 41}{space 1}   -0.99{col 50}{space 3}0.323{col 58}{space 4}-.1863927{col 71}{space 3} .0614913
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0851474{col 30}{space 2} .0452934{col 41}{space 1}   -1.88{col 50}{space 3}0.060{col 58}{space 4}-.1739208{col 71}{space 3} .0036259
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0524232{col 30}{space 2} .0369344{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0199669{col 71}{space 3} .1248132
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1033078{col 30}{space 2} .0275902{col 41}{space 1}   -3.74{col 50}{space 3}0.000{col 58}{space 4}-.1573836{col 71}{space 3} -.049232
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1462866{col 30}{space 2} .0294973{col 41}{space 1}    4.96{col 50}{space 3}0.000{col 58}{space 4} .0884729{col 71}{space 3} .2041002
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1652043{col 30}{space 2} .0430404{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0808466{col 71}{space 3}  .249562
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.1289342{col 30}{space 2} .1777006{col 41}{space 1}   -0.73{col 50}{space 3}0.468{col 58}{space 4} -.477221{col 71}{space 3} .2193527
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0335231{col 30}{space 2} .0604924{col 41}{space 1}   -0.55{col 50}{space 3}0.579{col 58}{space 4}-.1520861{col 71}{space 3} .0850398
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.0033553{col 30}{space 2} .0771947{col 41}{space 1}   -0.04{col 50}{space 3}0.965{col 58}{space 4}-.1546541{col 71}{space 3} .1479435
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0230671{col 30}{space 2} .0617441{col 41}{space 1}   -0.37{col 50}{space 3}0.709{col 58}{space 4}-.1440833{col 71}{space 3} .0979491
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2235382{col 30}{space 2} .0532937{col 41}{space 1}   -4.19{col 50}{space 3}0.000{col 58}{space 4}-.3279921{col 71}{space 3}-.1190844
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2721752{col 30}{space 2} .0174642{col 41}{space 1}   15.58{col 50}{space 3}0.000{col 58}{space 4}  .237946{col 71}{space 3} .3064044
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .5630036{col 30}{space 2} .0350039{col 41}{space 1}   16.08{col 50}{space 3}0.000{col 58}{space 4} .4943971{col 71}{space 3}   .63161
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .2735095{col 30}{space 2} .0285378{col 41}{space 1}    9.58{col 50}{space 3}0.000{col 58}{space 4} .2175763{col 71}{space 3} .3294426
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0144419{col 30}{space 2} .0664906{col 41}{space 1}    0.22{col 50}{space 3}0.828{col 58}{space 4}-.1158773{col 71}{space 3}  .144761
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .39556837
         {txt}sigma_e {c |} {res} 1.0803198
             {txt}rho {c |} {res} .11822185{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. xtreg hdd9_purchase  pdd9_2    $xlist  pdd9_mean $year_MALAWI if country==6, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,155
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,447

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0488                                         {txt}min = {res}         1
{txt}     between = {res}0.5059                                         {txt}avg = {res}       2.7
{txt}     overall = {res}0.4315                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  5461.59
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_2 {c |}{col 18}{res}{space 2}-.0122859{col 30}{space 2} .0169108{col 41}{space 1}   -0.73{col 50}{space 3}0.468{col 58}{space 4}-.0454304{col 71}{space 3} .0208585
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0171889{col 30}{space 2} .0101529{col 41}{space 1}    1.69{col 50}{space 3}0.090{col 58}{space 4}-.0027103{col 71}{space 3} .0370882
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.4055607{col 30}{space 2} .0859136{col 41}{space 1}   -4.72{col 50}{space 3}0.000{col 58}{space 4}-.5739483{col 71}{space 3} -.237173
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0072105{col 30}{space 2} .0015781{col 41}{space 1}   -4.57{col 50}{space 3}0.000{col 58}{space 4}-.0103036{col 71}{space 3}-.0041174
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1293879{col 30}{space 2}  .050701{col 41}{space 1}   -2.55{col 50}{space 3}0.011{col 58}{space 4}  -.22876{col 71}{space 3}-.0300158
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3041983{col 30}{space 2} .0516055{col 41}{space 1}    5.89{col 50}{space 3}0.000{col 58}{space 4} .2030534{col 71}{space 3} .4053431
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2183675{col 30}{space 2} .1458771{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.0675464{col 71}{space 3} .5042814
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .4297851{col 30}{space 2} .0604734{col 41}{space 1}    7.11{col 50}{space 3}0.000{col 58}{space 4} .3112593{col 71}{space 3} .5483108
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .5304345{col 30}{space 2} .0962794{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4} .3417304{col 71}{space 3} .7191385
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .317736{col 30}{space 2} .0649298{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4} .1904759{col 71}{space 3} .4449961
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3672773{col 30}{space 2} .0490494{col 41}{space 1}    7.49{col 50}{space 3}0.000{col 58}{space 4} .2711423{col 71}{space 3} .4634124
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0942493{col 30}{space 2} .0387118{col 41}{space 1}   -2.43{col 50}{space 3}0.015{col 58}{space 4}-.1701231{col 71}{space 3}-.0183755
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0104369{col 30}{space 2}  .029444{col 41}{space 1}   -0.35{col 50}{space 3}0.723{col 58}{space 4}-.0681462{col 71}{space 3} .0472723
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} -.005101{col 30}{space 2} .0572654{col 41}{space 1}   -0.09{col 50}{space 3}0.929{col 58}{space 4}-.1173391{col 71}{space 3}  .107137
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4603734{col 30}{space 2} .2375913{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4} -.005297{col 71}{space 3} .9260439
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5400978{col 30}{space 2} .0920042{col 41}{space 1}    5.87{col 50}{space 3}0.000{col 58}{space 4} .3597729{col 71}{space 3} .7204227
{txt}electricity_mean {c |}{col 18}{res}{space 2} .9049092{col 30}{space 2} .1273068{col 41}{space 1}    7.11{col 50}{space 3}0.000{col 58}{space 4} .6553925{col 71}{space 3} 1.154426
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .548971{col 30}{space 2} .0940249{col 41}{space 1}    5.84{col 50}{space 3}0.000{col 58}{space 4} .3646856{col 71}{space 3} .7332563
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .6750612{col 30}{space 2} .0822026{col 41}{space 1}    8.21{col 50}{space 3}0.000{col 58}{space 4}  .513947{col 71}{space 3} .8361753
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2472667{col 30}{space 2} .0249932{col 41}{space 1}   -9.89{col 50}{space 3}0.000{col 58}{space 4}-.2962524{col 71}{space 3}-.1982809
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2317679{col 30}{space 2} .0489227{col 41}{space 1}   -4.74{col 50}{space 3}0.000{col 58}{space 4}-.3276547{col 71}{space 3}-.1358812
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} -.011183{col 30}{space 2} .0400627{col 41}{space 1}   -0.28{col 50}{space 3}0.780{col 58}{space 4}-.0897045{col 71}{space 3} .0673385
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.476926{col 30}{space 2} .1088903{col 41}{space 1}   41.11{col 50}{space 3}0.000{col 58}{space 4} 4.263505{col 71}{space 3} 4.690347
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .94760357
         {txt}sigma_e {c |} {res}  1.489792
             {txt}rho {c |} {res} .28804231{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. rename  pdd9_2         pdd9_3
{res}{txt}
{com}. *Niger
. xtreg hdd9_own  pdd9_3    $xlist  pdd9_mean $year_NIGER if country==1, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,044
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,069

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1557                                         {txt}min = {res}         1
{txt}     between = {res}0.4767                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.4049                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  4771.79
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_3 {c |}{col 18}{res}{space 2} .1973853{col 30}{space 2} .0219255{col 41}{space 1}    9.00{col 50}{space 3}0.000{col 58}{space 4} .1544121{col 71}{space 3} .2403586
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0000582{col 30}{space 2} .0035628{col 41}{space 1}   -0.02{col 50}{space 3}0.987{col 58}{space 4}-.0070411{col 71}{space 3} .0069248
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0136811{col 30}{space 2} .0477215{col 41}{space 1}   -0.29{col 50}{space 3}0.774{col 58}{space 4}-.1072136{col 71}{space 3} .0798513
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.001344{col 30}{space 2}  .000783{col 41}{space 1}   -1.72{col 50}{space 3}0.086{col 58}{space 4}-.0028786{col 71}{space 3} .0001906
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1293763{col 30}{space 2} .0256726{col 41}{space 1}   -5.04{col 50}{space 3}0.000{col 58}{space 4}-.1796937{col 71}{space 3} -.079059
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0596942{col 30}{space 2} .0243584{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0119526{col 71}{space 3} .1074359
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0346525{col 30}{space 2} .0431278{col 41}{space 1}    0.80{col 50}{space 3}0.422{col 58}{space 4}-.0498765{col 71}{space 3} .1191815
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.1009946{col 30}{space 2}  .040821{col 41}{space 1}   -2.47{col 50}{space 3}0.013{col 58}{space 4}-.1810023{col 71}{space 3}-.0209869
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1047576{col 30}{space 2} .0399843{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4} .0263899{col 71}{space 3} .1831253
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1021303{col 30}{space 2} .0434451{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0169795{col 71}{space 3}  .187281
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0031368{col 30}{space 2} .0377983{col 41}{space 1}   -0.08{col 50}{space 3}0.934{col 58}{space 4}  -.07722{col 71}{space 3} .0709465
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.003441{col 30}{space 2}  .028432{col 41}{space 1}   -0.12{col 50}{space 3}0.904{col 58}{space 4}-.0591668{col 71}{space 3} .0522847
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0006563{col 30}{space 2} .0011029{col 41}{space 1}    0.60{col 50}{space 3}0.552{col 58}{space 4}-.0015053{col 71}{space 3} .0028179
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3706267{col 30}{space 2} .1470621{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0823904{col 71}{space 3}  .658863
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0753269{col 30}{space 2} .0525013{col 41}{space 1}   -1.43{col 50}{space 3}0.151{col 58}{space 4}-.1782275{col 71}{space 3} .0275737
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0638446{col 30}{space 2} .0509537{col 41}{space 1}   -1.25{col 50}{space 3}0.210{col 58}{space 4}-.1637119{col 71}{space 3} .0360228
{txt}electricity_mean {c |}{col 18}{res}{space 2} -.237074{col 30}{space 2} .0504786{col 41}{space 1}   -4.70{col 50}{space 3}0.000{col 58}{space 4}-.3360102{col 71}{space 3}-.1381379
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1731654{col 30}{space 2} .0494818{col 41}{space 1}   -3.50{col 50}{space 3}0.000{col 58}{space 4} -.270148{col 71}{space 3}-.0761828
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0647682{col 30}{space 2} .0460524{col 41}{space 1}   -1.41{col 50}{space 3}0.160{col 58}{space 4}-.1550292{col 71}{space 3} .0254928
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2307013{col 30}{space 2}  .023388{col 41}{space 1}    9.86{col 50}{space 3}0.000{col 58}{space 4} .1848617{col 71}{space 3}  .276541
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}  .323043{col 30}{space 2} .0191127{col 41}{space 1}   16.90{col 50}{space 3}0.000{col 58}{space 4} .2855827{col 71}{space 3} .3605033
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1166266{col 30}{space 2} .0555234{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4} .0078026{col 71}{space 3} .2254505
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .25712132
         {txt}sigma_e {c |} {res} .76186721
             {txt}rho {c |} {res} .10225205{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. xtreg hdd9_purchase  pdd9_3    $xlist  pdd9_mean $year_NIGER if country==1, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,044
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,069

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0217                                         {txt}min = {res}         1
{txt}     between = {res}0.3097                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.2440                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  2323.27
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_3 {c |}{col 18}{res}{space 2} .2281132{col 30}{space 2} .0378599{col 41}{space 1}    6.03{col 50}{space 3}0.000{col 58}{space 4} .1539092{col 71}{space 3} .3023173
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0167356{col 30}{space 2} .0072052{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0026136{col 71}{space 3} .0308576
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0782751{col 30}{space 2} .1071147{col 41}{space 1}   -0.73{col 50}{space 3}0.465{col 58}{space 4}-.2882161{col 71}{space 3} .1316658
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0008318{col 30}{space 2} .0015999{col 41}{space 1}    0.52{col 50}{space 3}0.603{col 58}{space 4}-.0023039{col 71}{space 3} .0039676
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0882308{col 30}{space 2} .0636703{col 41}{space 1}    1.39{col 50}{space 3}0.166{col 58}{space 4}-.0365607{col 71}{space 3} .2130224
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3640223{col 30}{space 2} .0482295{col 41}{space 1}    7.55{col 50}{space 3}0.000{col 58}{space 4} .2694943{col 71}{space 3} .4585503
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2332104{col 30}{space 2} .0998436{col 41}{space 1}    2.34{col 50}{space 3}0.020{col 58}{space 4} .0375205{col 71}{space 3} .4289003
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1478941{col 30}{space 2} .0814572{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4} -.011759{col 71}{space 3} .3075473
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .224841{col 30}{space 2} .1089059{col 41}{space 1}    2.06{col 50}{space 3}0.039{col 58}{space 4} .0113893{col 71}{space 3} .4382927
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2835598{col 30}{space 2} .0890238{col 41}{space 1}    3.19{col 50}{space 3}0.001{col 58}{space 4} .1090764{col 71}{space 3} .4580433
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1737196{col 30}{space 2} .0722002{col 41}{space 1}   -2.41{col 50}{space 3}0.016{col 58}{space 4}-.3152295{col 71}{space 3}-.0322098
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1465092{col 30}{space 2} .0502486{col 41}{space 1}   -2.92{col 50}{space 3}0.004{col 58}{space 4}-.2449946{col 71}{space 3}-.0480237
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0005281{col 30}{space 2} .0016676{col 41}{space 1}   -0.32{col 50}{space 3}0.751{col 58}{space 4}-.0037966{col 71}{space 3} .0027403
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0697816{col 30}{space 2} .2433595{col 41}{space 1}    0.29{col 50}{space 3}0.774{col 58}{space 4}-.4071943{col 71}{space 3} .5467576
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1456749{col 30}{space 2} .1251222{col 41}{space 1}    1.16{col 50}{space 3}0.244{col 58}{space 4}-.0995601{col 71}{space 3} .3909098
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4665053{col 30}{space 2}  .101602{col 41}{space 1}    4.59{col 50}{space 3}0.000{col 58}{space 4}  .267369{col 71}{space 3} .6656416
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6709489{col 30}{space 2} .1296436{col 41}{space 1}    5.18{col 50}{space 3}0.000{col 58}{space 4}  .416852{col 71}{space 3} .9250457
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2765942{col 30}{space 2} .1123867{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4} .0563203{col 71}{space 3} .4968682
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5980706{col 30}{space 2} .0894371{col 41}{space 1}    6.69{col 50}{space 3}0.000{col 58}{space 4} .4227772{col 71}{space 3}  .773364
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.3293337{col 30}{space 2} .0433456{col 41}{space 1}   -7.60{col 50}{space 3}0.000{col 58}{space 4}-.4142895{col 71}{space 3}-.2443779
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0191601{col 30}{space 2} .0396751{col 41}{space 1}    0.48{col 50}{space 3}0.629{col 58}{space 4}-.0586018{col 71}{space 3} .0969219
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.218393{col 30}{space 2} .1175928{col 41}{space 1}   35.87{col 50}{space 3}0.000{col 58}{space 4} 3.987916{col 71}{space 3} 4.448871
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72100716
         {txt}sigma_e {c |} {res} 1.5029883
             {txt}rho {c |} {res} .18707595{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est8
{txt}
{com}. 
. rename  pdd9_3       pdd9_4
{res}{txt}
{com}. *Nigeria
. xtreg hdd9_own  pdd9_4   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    18,429
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,218

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0993                                         {txt}min = {res}         1
{txt}     between = {res}0.4545                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.4045                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res} 11082.69
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,218} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_4 {c |}{col 18}{res}{space 2}  .232078{col 30}{space 2}  .011813{col 41}{space 1}   19.65{col 50}{space 3}0.000{col 58}{space 4}  .208925{col 71}{space 3}  .255231
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .010716{col 30}{space 2} .0029827{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4}   .00487{col 71}{space 3}  .016562
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0363237{col 30}{space 2} .0317138{col 41}{space 1}   -1.15{col 50}{space 3}0.252{col 58}{space 4}-.0984816{col 71}{space 3} .0258341
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0007506{col 30}{space 2} .0005705{col 41}{space 1}    1.32{col 50}{space 3}0.188{col 58}{space 4}-.0003676{col 71}{space 3} .0018688
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0428719{col 30}{space 2} .0228444{col 41}{space 1}   -1.88{col 50}{space 3}0.061{col 58}{space 4}-.0876462{col 71}{space 3} .0019024
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0261416{col 30}{space 2} .0193083{col 41}{space 1}   -1.35{col 50}{space 3}0.176{col 58}{space 4}-.0639851{col 71}{space 3} .0117019
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0533326{col 30}{space 2} .0267002{col 41}{space 1}   -2.00{col 50}{space 3}0.046{col 58}{space 4} -.105664{col 71}{space 3}-.0010012
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0543923{col 30}{space 2} .0265015{col 41}{space 1}    2.05{col 50}{space 3}0.040{col 58}{space 4} .0024502{col 71}{space 3} .1063343
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0047538{col 30}{space 2} .0323875{col 41}{space 1}   -0.15{col 50}{space 3}0.883{col 58}{space 4} -.068232{col 71}{space 3} .0587245
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0025082{col 30}{space 2} .0293049{col 41}{space 1}    0.09{col 50}{space 3}0.932{col 58}{space 4}-.0549282{col 71}{space 3} .0599447
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0223209{col 30}{space 2} .0279333{col 41}{space 1}    0.80{col 50}{space 3}0.424{col 58}{space 4}-.0324273{col 71}{space 3}  .077069
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1046307{col 30}{space 2} .0363266{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0334319{col 71}{space 3} .1758296
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0158071{col 30}{space 2} .0074746{col 41}{space 1}    2.11{col 50}{space 3}0.034{col 58}{space 4} .0011572{col 71}{space 3} .0304569
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1640597{col 30}{space 2} .0461682{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4} .0735718{col 71}{space 3} .2545476
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2228397{col 30}{space 2} .0367329{col 41}{space 1}    6.07{col 50}{space 3}0.000{col 58}{space 4} .1508446{col 71}{space 3} .2948348
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0725493{col 30}{space 2} .0393678{col 41}{space 1}    1.84{col 50}{space 3}0.065{col 58}{space 4}-.0046102{col 71}{space 3} .1497088
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2989324{col 30}{space 2}  .040759{col 41}{space 1}   -7.33{col 50}{space 3}0.000{col 58}{space 4}-.3788186{col 71}{space 3}-.2190462
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1977187{col 30}{space 2} .0386889{col 41}{space 1}   -5.11{col 50}{space 3}0.000{col 58}{space 4}-.2735474{col 71}{space 3}-.1218899
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1885144{col 30}{space 2} .0352227{col 41}{space 1}   -5.35{col 50}{space 3}0.000{col 58}{space 4}-.2575496{col 71}{space 3}-.1194792
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2117643{col 30}{space 2} .0137466{col 41}{space 1}   15.40{col 50}{space 3}0.000{col 58}{space 4} .1848214{col 71}{space 3} .2387072
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5233821{col 30}{space 2}  .022234{col 41}{space 1}  -23.54{col 50}{space 3}0.000{col 58}{space 4}  -.56696{col 71}{space 3}-.4798043
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.2997497{col 30}{space 2} .0219591{col 41}{space 1}  -13.65{col 50}{space 3}0.000{col 58}{space 4}-.3427887{col 71}{space 3}-.2567106
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3180665{col 30}{space 2} .0222853{col 41}{space 1}  -14.27{col 50}{space 3}0.000{col 58}{space 4}-.3617449{col 71}{space 3}-.2743882
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .7727287{col 30}{space 2} .0459978{col 41}{space 1}   16.80{col 50}{space 3}0.000{col 58}{space 4} .6825747{col 71}{space 3} .8628826
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .55143368
         {txt}sigma_e {c |} {res} .85452267
             {txt}rho {c |} {res} .29399845{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est9
{txt}
{com}. xtreg hdd9_purchase  pdd9_4    $xlist  pdd9_mean $year_NIGERIA if country==2, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    18,429
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,218

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0223                                         {txt}min = {res}         1
{txt}     between = {res}0.3751                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.3244                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  6343.17
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,218} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_4 {c |}{col 18}{res}{space 2} .0154161{col 30}{space 2} .0159749{col 41}{space 1}    0.97{col 50}{space 3}0.335{col 58}{space 4}-.0158942{col 71}{space 3} .0467264
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0088861{col 30}{space 2} .0049866{col 41}{space 1}   -1.78{col 50}{space 3}0.075{col 58}{space 4}-.0186597{col 71}{space 3} .0008874
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0758525{col 30}{space 2} .0552353{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0324067{col 71}{space 3} .1841118
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0007798{col 30}{space 2} .0010176{col 41}{space 1}    0.77{col 50}{space 3}0.443{col 58}{space 4}-.0012146{col 71}{space 3} .0027742
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2144079{col 30}{space 2} .0403716{col 41}{space 1}    5.31{col 50}{space 3}0.000{col 58}{space 4}  .135281{col 71}{space 3} .2935349
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2663009{col 30}{space 2}  .030417{col 41}{space 1}    8.76{col 50}{space 3}0.000{col 58}{space 4} .2066847{col 71}{space 3} .3259171
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0505892{col 30}{space 2}  .042032{col 41}{space 1}    1.20{col 50}{space 3}0.229{col 58}{space 4}-.0317919{col 71}{space 3} .1329704
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2243559{col 30}{space 2} .0422463{col 41}{space 1}    5.31{col 50}{space 3}0.000{col 58}{space 4} .1415546{col 71}{space 3} .3071572
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1335494{col 30}{space 2} .0497534{col 41}{space 1}    2.68{col 50}{space 3}0.007{col 58}{space 4} .0360345{col 71}{space 3} .2310644
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2284137{col 30}{space 2} .0530897{col 41}{space 1}    4.30{col 50}{space 3}0.000{col 58}{space 4} .1243598{col 71}{space 3} .3324676
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3385972{col 30}{space 2}   .04379{col 41}{space 1}    7.73{col 50}{space 3}0.000{col 58}{space 4} .2527705{col 71}{space 3}  .424424
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0960612{col 30}{space 2} .0531849{col 41}{space 1}   -1.81{col 50}{space 3}0.071{col 58}{space 4}-.2003017{col 71}{space 3} .0081793
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0186462{col 30}{space 2} .0113527{col 41}{space 1}   -1.64{col 50}{space 3}0.100{col 58}{space 4} -.040897{col 71}{space 3} .0036046
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2067037{col 30}{space 2} .0657966{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4} .0777447{col 71}{space 3} .3356627
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.1222089{col 30}{space 2} .0584666{col 41}{space 1}   -2.09{col 50}{space 3}0.037{col 58}{space 4}-.2368013{col 71}{space 3}-.0076164
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7794276{col 30}{space 2} .0644403{col 41}{space 1}   12.10{col 50}{space 3}0.000{col 58}{space 4} .6531268{col 71}{space 3} .9057283
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.042761{col 30}{space 2} .0640976{col 41}{space 1}   16.27{col 50}{space 3}0.000{col 58}{space 4} .9171315{col 71}{space 3}  1.16839
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3703755{col 30}{space 2} .0701631{col 41}{space 1}    5.28{col 50}{space 3}0.000{col 58}{space 4} .2328584{col 71}{space 3} .5078926
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .133627{col 30}{space 2} .0573514{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0212203{col 71}{space 3} .2460338
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1722757{col 30}{space 2} .0205091{col 41}{space 1}   -8.40{col 50}{space 3}0.000{col 58}{space 4}-.2124727{col 71}{space 3}-.1320787
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2232765{col 30}{space 2} .0347917{col 41}{space 1}   -6.42{col 50}{space 3}0.000{col 58}{space 4}-.2914669{col 71}{space 3}-.1550861
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.3088386{col 30}{space 2} .0344666{col 41}{space 1}   -8.96{col 50}{space 3}0.000{col 58}{space 4} -.376392{col 71}{space 3}-.2412852
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0575336{col 30}{space 2} .0343788{col 41}{space 1}   -1.67{col 50}{space 3}0.094{col 58}{space 4}-.1249148{col 71}{space 3} .0098475
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.745021{col 30}{space 2} .0820178{col 41}{space 1}   45.66{col 50}{space 3}0.000{col 58}{space 4} 3.584269{col 71}{space 3} 3.905773
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .95365027
         {txt}sigma_e {c |} {res} 1.3723453
             {txt}rho {c |} {res} .32564281{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est10
{txt}
{com}. 
. 
. rename  pdd9_4       pdd9_5
{res}{txt}
{com}. *Tanzania
. xtreg hdd9_own  pdd9_5    $xlist  pdd9_mean $year_TANZANIA if country==5, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    17,046
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,817

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1105                                         {txt}min = {res}         1
{txt}     between = {res}0.6556                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.5796                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res} 20814.27
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,817} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_5 {c |}{col 18}{res}{space 2} .2953455{col 30}{space 2} .0120988{col 41}{space 1}   24.41{col 50}{space 3}0.000{col 58}{space 4} .2716323{col 71}{space 3} .3190587
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0266378{col 30}{space 2} .0041994{col 41}{space 1}    6.34{col 50}{space 3}0.000{col 58}{space 4} .0184071{col 71}{space 3} .0348686
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0440803{col 30}{space 2} .0418239{col 41}{space 1}   -1.05{col 50}{space 3}0.292{col 58}{space 4}-.1260537{col 71}{space 3}  .037893
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0020322{col 30}{space 2} .0007099{col 41}{space 1}   -2.86{col 50}{space 3}0.004{col 58}{space 4}-.0034237{col 71}{space 3}-.0006408
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0622128{col 30}{space 2}  .022594{col 41}{space 1}   -2.75{col 50}{space 3}0.006{col 58}{space 4}-.1064963{col 71}{space 3}-.0179293
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0332891{col 30}{space 2} .0260734{col 41}{space 1}    1.28{col 50}{space 3}0.202{col 58}{space 4}-.0178138{col 71}{space 3}  .084392
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0668397{col 30}{space 2} .0549528{col 41}{space 1}    1.22{col 50}{space 3}0.224{col 58}{space 4}-.0408657{col 71}{space 3} .1745451
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0506504{col 30}{space 2} .0370027{col 41}{space 1}   -1.37{col 50}{space 3}0.171{col 58}{space 4}-.1231743{col 71}{space 3} .0218735
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1555193{col 30}{space 2} .0435875{col 41}{space 1}   -3.57{col 50}{space 3}0.000{col 58}{space 4}-.2409493{col 71}{space 3}-.0700893
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} -.023113{col 30}{space 2} .0280287{col 41}{space 1}   -0.82{col 50}{space 3}0.410{col 58}{space 4}-.0780483{col 71}{space 3} .0318223
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0155198{col 30}{space 2} .0290792{col 41}{space 1}    0.53{col 50}{space 3}0.594{col 58}{space 4}-.0414743{col 71}{space 3} .0725139
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0790391{col 30}{space 2} .0234674{col 41}{space 1}   -3.37{col 50}{space 3}0.001{col 58}{space 4}-.1250344{col 71}{space 3}-.0330438
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0156232{col 30}{space 2} .0048243{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .0061679{col 71}{space 3} .0250786
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2188395{col 30}{space 2} .0292999{col 41}{space 1}    7.47{col 50}{space 3}0.000{col 58}{space 4} .1614126{col 71}{space 3} .2762663
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0012141{col 30}{space 2} .0660368{col 41}{space 1}   -0.02{col 50}{space 3}0.985{col 58}{space 4}-.1306438{col 71}{space 3} .1282156
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0890016{col 30}{space 2} .0484716{col 41}{space 1}   -1.84{col 50}{space 3}0.066{col 58}{space 4}-.1840042{col 71}{space 3}  .006001
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0276333{col 30}{space 2} .0508055{col 41}{space 1}    0.54{col 50}{space 3}0.587{col 58}{space 4}-.0719436{col 71}{space 3} .1272103
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2015791{col 30}{space 2}  .037325{col 41}{space 1}   -5.40{col 50}{space 3}0.000{col 58}{space 4}-.2747348{col 71}{space 3}-.1284234
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2641617{col 30}{space 2} .0376173{col 41}{space 1}   -7.02{col 50}{space 3}0.000{col 58}{space 4}-.3378902{col 71}{space 3}-.1904332
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2623017{col 30}{space 2} .0134133{col 41}{space 1}   19.56{col 50}{space 3}0.000{col 58}{space 4} .2360121{col 71}{space 3} .2885914
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0514387{col 30}{space 2} .0246591{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0031077{col 71}{space 3} .0997697
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0307463{col 30}{space 2} .0203743{col 41}{space 1}    1.51{col 50}{space 3}0.131{col 58}{space 4}-.0091865{col 71}{space 3} .0706791
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} -.002136{col 30}{space 2} .0226813{col 41}{space 1}   -0.09{col 50}{space 3}0.925{col 58}{space 4}-.0465907{col 71}{space 3} .0423186
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .4826065{col 30}{space 2} .0539877{col 41}{space 1}    8.94{col 50}{space 3}0.000{col 58}{space 4} .3767926{col 71}{space 3} .5884205
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .44195664
         {txt}sigma_e {c |} {res} .99908067
             {txt}rho {c |} {res} .16365954{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est11
{txt}
{com}. xtreg hdd9_purchase  pdd9_5    $xlist  pdd9_mean $year_TANZANIA if country==5, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    17,046
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,817

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0191                                         {txt}min = {res}         1
{txt}     between = {res}0.4654                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.4274                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  9660.62
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,817} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_5 {c |}{col 18}{res}{space 2}-.0010869{col 30}{space 2} .0144521{col 41}{space 1}   -0.08{col 50}{space 3}0.940{col 58}{space 4}-.0294124{col 71}{space 3} .0272386
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0099436{col 30}{space 2} .0063163{col 41}{space 1}   -1.57{col 50}{space 3}0.115{col 58}{space 4}-.0223233{col 71}{space 3} .0024362
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0385898{col 30}{space 2} .0684059{col 41}{space 1}   -0.56{col 50}{space 3}0.573{col 58}{space 4} -.172663{col 71}{space 3} .0954833
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.002148{col 30}{space 2} .0011227{col 41}{space 1}   -1.91{col 50}{space 3}0.056{col 58}{space 4}-.0043485{col 71}{space 3} .0000525
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0588771{col 30}{space 2} .0366525{col 41}{space 1}    1.61{col 50}{space 3}0.108{col 58}{space 4}-.0129604{col 71}{space 3} .1307147
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .4303771{col 30}{space 2} .0382945{col 41}{space 1}   11.24{col 50}{space 3}0.000{col 58}{space 4} .3553214{col 71}{space 3} .5054329
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0776333{col 30}{space 2} .0775476{col 41}{space 1}    1.00{col 50}{space 3}0.317{col 58}{space 4}-.0743572{col 71}{space 3} .2296238
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .4007154{col 30}{space 2} .0471971{col 41}{space 1}    8.49{col 50}{space 3}0.000{col 58}{space 4} .3082108{col 71}{space 3}   .49322
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .098917{col 30}{space 2}   .06193{col 41}{space 1}    1.60{col 50}{space 3}0.110{col 58}{space 4}-.0224635{col 71}{space 3} .2202975
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2054413{col 30}{space 2} .0372556{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4} .1324217{col 71}{space 3} .2784609
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .318705{col 30}{space 2} .0408313{col 41}{space 1}    7.81{col 50}{space 3}0.000{col 58}{space 4} .2386772{col 71}{space 3} .3987328
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0682691{col 30}{space 2} .0337579{col 41}{space 1}   -2.02{col 50}{space 3}0.043{col 58}{space 4}-.1344334{col 71}{space 3}-.0021047
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0064188{col 30}{space 2} .0043609{col 41}{space 1}   -1.47{col 50}{space 3}0.141{col 58}{space 4} -.014966{col 71}{space 3} .0021285
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1093497{col 30}{space 2} .0365908{col 41}{space 1}   -2.99{col 50}{space 3}0.003{col 58}{space 4}-.1810664{col 71}{space 3}-.0376329
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .5525427{col 30}{space 2} .1011264{col 41}{space 1}    5.46{col 50}{space 3}0.000{col 58}{space 4} .3543386{col 71}{space 3} .7507468
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6919189{col 30}{space 2} .0666437{col 41}{space 1}   10.38{col 50}{space 3}0.000{col 58}{space 4} .5612997{col 71}{space 3} .8225381
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8087104{col 30}{space 2} .0771103{col 41}{space 1}   10.49{col 50}{space 3}0.000{col 58}{space 4}  .657577{col 71}{space 3} .9598439
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1999892{col 30}{space 2}  .054446{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4}  .093277{col 71}{space 3} .3067014
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5054748{col 30}{space 2} .0565759{col 41}{space 1}    8.93{col 50}{space 3}0.000{col 58}{space 4} .3945881{col 71}{space 3} .6163616
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.3103687{col 30}{space 2} .0173559{col 41}{space 1}  -17.88{col 50}{space 3}0.000{col 58}{space 4}-.3443856{col 71}{space 3}-.2763518
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0047018{col 30}{space 2} .0334595{col 41}{space 1}   -0.14{col 50}{space 3}0.888{col 58}{space 4}-.0702813{col 71}{space 3} .0608777
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0412714{col 30}{space 2} .0286208{col 41}{space 1}   -1.44{col 50}{space 3}0.149{col 58}{space 4}-.0973671{col 71}{space 3} .0148243
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0503713{col 30}{space 2} .0349371{col 41}{space 1}   -1.44{col 50}{space 3}0.149{col 58}{space 4}-.1188467{col 71}{space 3} .0181041
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.645053{col 30}{space 2} .0854022{col 41}{space 1}   42.68{col 50}{space 3}0.000{col 58}{space 4} 3.477668{col 71}{space 3} 3.812438
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} 1.0749284
         {txt}sigma_e {c |} {res} 1.3411357
             {txt}rho {c |} {res} .39113935{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est12
{txt}
{com}. 
. rename  pdd9_5       pdd9_6
{res}{txt}
{com}. *Uganda
. xtreg hdd9_own  pdd9_6    $xlist  pdd9_mean $year_UGANDA if country==4, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    20,293
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,105

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0727                                         {txt}min = {res}         1
{txt}     between = {res}0.6607                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.4725                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res} 17543.40
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,105} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_6 {c |}{col 18}{res}{space 2} .2260514{col 30}{space 2} .0104819{col 41}{space 1}   21.57{col 50}{space 3}0.000{col 58}{space 4} .2055072{col 71}{space 3} .2465956
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0328326{col 30}{space 2} .0045105{col 41}{space 1}    7.28{col 50}{space 3}0.000{col 58}{space 4} .0239922{col 71}{space 3}  .041673
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0413164{col 30}{space 2}  .046077{col 41}{space 1}   -0.90{col 50}{space 3}0.370{col 58}{space 4}-.1316258{col 71}{space 3} .0489929
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .002846{col 30}{space 2} .0008116{col 41}{space 1}    3.51{col 50}{space 3}0.000{col 58}{space 4} .0012553{col 71}{space 3} .0044367
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0129076{col 30}{space 2} .0257692{col 41}{space 1}   -0.50{col 50}{space 3}0.616{col 58}{space 4}-.0634143{col 71}{space 3} .0375991
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1699218{col 30}{space 2} .0264035{col 41}{space 1}    6.44{col 50}{space 3}0.000{col 58}{space 4} .1181719{col 71}{space 3} .2216716
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0143539{col 30}{space 2} .0457923{col 41}{space 1}    0.31{col 50}{space 3}0.754{col 58}{space 4}-.0753974{col 71}{space 3} .1041052
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1096989{col 30}{space 2} .0311658{col 41}{space 1}    3.52{col 50}{space 3}0.000{col 58}{space 4}  .048615{col 71}{space 3} .1707828
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .069206{col 30}{space 2} .0305109{col 41}{space 1}    2.27{col 50}{space 3}0.023{col 58}{space 4} .0094058{col 71}{space 3} .1290063
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.1693952{col 30}{space 2} .0246971{col 41}{space 1}   -6.86{col 50}{space 3}0.000{col 58}{space 4}-.2178005{col 71}{space 3}-.1209898
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0262687{col 30}{space 2} .0280844{col 41}{space 1}   -0.94{col 50}{space 3}0.350{col 58}{space 4} -.081313{col 71}{space 3} .0287756
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0224151{col 30}{space 2} .0226847{col 41}{space 1}   -0.99{col 50}{space 3}0.323{col 58}{space 4}-.0668763{col 71}{space 3} .0220462
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0036948{col 30}{space 2} .0019723{col 41}{space 1}    1.87{col 50}{space 3}0.061{col 58}{space 4}-.0001708{col 71}{space 3} .0075603
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1950911{col 30}{space 2} .0252482{col 41}{space 1}    7.73{col 50}{space 3}0.000{col 58}{space 4} .1456056{col 71}{space 3} .2445766
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0685499{col 30}{space 2} .0671226{col 41}{space 1}    1.02{col 50}{space 3}0.307{col 58}{space 4} -.063008{col 71}{space 3} .2001078
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0160592{col 30}{space 2} .0520765{col 41}{space 1}    0.31{col 50}{space 3}0.758{col 58}{space 4}-.0860088{col 71}{space 3} .1181272
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1092212{col 30}{space 2} .0514522{col 41}{space 1}   -2.12{col 50}{space 3}0.034{col 58}{space 4}-.2100657{col 71}{space 3}-.0083767
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1803489{col 30}{space 2} .0429307{col 41}{space 1}   -4.20{col 50}{space 3}0.000{col 58}{space 4}-.2644915{col 71}{space 3}-.0962064
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3467825{col 30}{space 2}   .04381{col 41}{space 1}   -7.92{col 50}{space 3}0.000{col 58}{space 4}-.4326485{col 71}{space 3}-.2609165
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .4590369{col 30}{space 2} .0137037{col 41}{space 1}   33.50{col 50}{space 3}0.000{col 58}{space 4} .4321782{col 71}{space 3} .4858956
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0946885{col 30}{space 2} .0280405{col 41}{space 1}   -3.38{col 50}{space 3}0.001{col 58}{space 4}-.1496469{col 71}{space 3}-.0397301
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .1218857{col 30}{space 2} .0281883{col 41}{space 1}    4.32{col 50}{space 3}0.000{col 58}{space 4} .0666376{col 71}{space 3} .1771339
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .357557{col 30}{space 2} .0275492{col 41}{space 1}   12.98{col 50}{space 3}0.000{col 58}{space 4} .3035614{col 71}{space 3} .4115525
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .2216119{col 30}{space 2} .0268278{col 41}{space 1}    8.26{col 50}{space 3}0.000{col 58}{space 4} .1690304{col 71}{space 3} .2741934
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3173685{col 30}{space 2} .0266506{col 41}{space 1}   11.91{col 50}{space 3}0.000{col 58}{space 4} .2651343{col 71}{space 3} .3696027
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0526347{col 30}{space 2} .0642385{col 41}{space 1}    0.82{col 50}{space 3}0.413{col 58}{space 4}-.0732706{col 71}{space 3} .1785399
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .54500537
         {txt}sigma_e {c |} {res} 1.1715101
             {txt}rho {c |} {res}  .1779196{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est13
{txt}
{com}. xtreg hdd9_purchase  pdd9_6    $xlist  pdd9_mean $year_UGANDA if country==4, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    20,293
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,105

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0377                                         {txt}min = {res}         1
{txt}     between = {res}0.4310                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.3084                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  4916.09
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,105} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_6 {c |}{col 18}{res}{space 2} -.005009{col 30}{space 2} .0119508{col 41}{space 1}   -0.42{col 50}{space 3}0.675{col 58}{space 4}-.0284323{col 71}{space 3} .0184142
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0096666{col 30}{space 2} .0060922{col 41}{space 1}    1.59{col 50}{space 3}0.113{col 58}{space 4} -.002274{col 71}{space 3} .0216071
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0438789{col 30}{space 2} .0640744{col 41}{space 1}    0.68{col 50}{space 3}0.493{col 58}{space 4}-.0817045{col 71}{space 3} .1694624
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0068861{col 30}{space 2} .0012157{col 41}{space 1}   -5.66{col 50}{space 3}0.000{col 58}{space 4}-.0092689{col 71}{space 3}-.0045033
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .052448{col 30}{space 2} .0380617{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0221515{col 71}{space 3} .1270476
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2260638{col 30}{space 2} .0348022{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4} .1578527{col 71}{space 3} .2942749
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2641742{col 30}{space 2} .0579825{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .1505306{col 71}{space 3} .3778177
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2844343{col 30}{space 2} .0379622{col 41}{space 1}    7.49{col 50}{space 3}0.000{col 58}{space 4} .2100297{col 71}{space 3} .3588389
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4591086{col 30}{space 2} .0392584{col 41}{space 1}   11.69{col 50}{space 3}0.000{col 58}{space 4} .3821636{col 71}{space 3} .5360536
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1976331{col 30}{space 2} .0310657{col 41}{space 1}    6.36{col 50}{space 3}0.000{col 58}{space 4} .1367454{col 71}{space 3} .2585209
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2783542{col 30}{space 2} .0336193{col 41}{space 1}    8.28{col 50}{space 3}0.000{col 58}{space 4} .2124616{col 71}{space 3} .3442467
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0247614{col 30}{space 2}  .027121{col 41}{space 1}    0.91{col 50}{space 3}0.361{col 58}{space 4}-.0283948{col 71}{space 3} .0779177
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003888{col 30}{space 2}  .001864{col 41}{space 1}    0.21{col 50}{space 3}0.835{col 58}{space 4}-.0032645{col 71}{space 3} .0040421
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1238323{col 30}{space 2} .0325821{col 41}{space 1}   -3.80{col 50}{space 3}0.000{col 58}{space 4}-.1876919{col 71}{space 3}-.0599726
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1817586{col 30}{space 2} .0963568{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4}-.0070973{col 71}{space 3} .3706145
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5067038{col 30}{space 2} .0700418{col 41}{space 1}    7.23{col 50}{space 3}0.000{col 58}{space 4} .3694243{col 71}{space 3} .6439833
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4959422{col 30}{space 2} .0757658{col 41}{space 1}    6.55{col 50}{space 3}0.000{col 58}{space 4}  .347444{col 71}{space 3} .6444404
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4181632{col 30}{space 2}  .063041{col 41}{space 1}    6.63{col 50}{space 3}0.000{col 58}{space 4}  .294605{col 71}{space 3} .5417214
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .7719908{col 30}{space 2} .0612551{col 41}{space 1}   12.60{col 50}{space 3}0.000{col 58}{space 4} .6519329{col 71}{space 3} .8920486
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} -.273935{col 30}{space 2} .0179865{col 41}{space 1}  -15.23{col 50}{space 3}0.000{col 58}{space 4} -.309188{col 71}{space 3} -.238682
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1576228{col 30}{space 2} .0352225{col 41}{space 1}   -4.48{col 50}{space 3}0.000{col 58}{space 4}-.2266576{col 71}{space 3} -.088588
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} -.137737{col 30}{space 2} .0348587{col 41}{space 1}   -3.95{col 50}{space 3}0.000{col 58}{space 4}-.2060587{col 71}{space 3}-.0694153
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .2182982{col 30}{space 2} .0350614{col 41}{space 1}    6.23{col 50}{space 3}0.000{col 58}{space 4} .1495791{col 71}{space 3} .2870173
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0266362{col 30}{space 2} .0348869{col 41}{space 1}    0.76{col 50}{space 3}0.445{col 58}{space 4}-.0417409{col 71}{space 3} .0950132
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2}  .167045{col 30}{space 2}  .033402{col 41}{space 1}    5.00{col 50}{space 3}0.000{col 58}{space 4} .1015783{col 71}{space 3} .2325117
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.311555{col 30}{space 2} .0966084{col 41}{space 1}   34.28{col 50}{space 3}0.000{col 58}{space 4} 3.122206{col 71}{space 3} 3.500904
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} 1.0493206
         {txt}sigma_e {c |} {res} 1.4522365
             {txt}rho {c |} {res} .34300669{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est14
{txt}
{com}. 
. coefplot (est1, label("HDDS from own production") msymbol(d) mlcolor(red%80) mfcolor(white)    ) (est2, label("") msymbol(s) mlcolor(navy) mfcolor(white)  )    (est3, label("") msymbol(d) mlcolor(red%80) mfcolor(white) ) (est4, label("") msymbol(s) mlcolor(navy) mfcolor(white)) ///    
>  (est5,label("") msymbol(d) mlcolor(red%80) mfcolor(white)) (est6,  label("") msymbol(s) mlcolor(navy) mfcolor(white))   (est7, label("") msymbol(d) mlcolor(red%80) mfcolor(white)  )  (est8, label("HDDS from market purchase") msymbol(s) mlcolor(navy) mfcolor(white)) /// 
>  (est9, label("") msymbol(d) mlcolor(red%80) mfcolor(white)) (est10, label("") msymbol(s) mlcolor(navy) mfcolor(white))   (est11, label("") msymbol(d) mlcolor(red%80) mfcolor(white)  )  (est12, label("") msymbol(s) mlcolor(navy) mfcolor(white)) /// 
>  (est13, label("") msymbol(d) mlcolor(red%80) mfcolor(white)) (est14, label("") msymbol(s) mlcolor(navy) mfcolor(white))  /// 
> ,  keep(pdd9 pdd9_1 pdd9_2 pdd9_3  pdd9_4 pdd9_5 pdd9_6) vertical ciopts(lcolor(grey%50)  recast(rcap))  ///
> legend(  size(small) rows(2) nobox region(color(ltbluishgray) lstyle(none))) ///  
> xmtick(0.6 1.6 2.8 4 5.1 6.2 7.4) xlabel( 0.6 "All countries" 1.6 "Ethiopia" 2.8 "Malawi" 4 "Niger"    5.1 "Nigeria" 6.2 "Tanzania" 7.4 "Uganda", labsize(small)) xscale(r(0(0.5)3.5)) ylabel(-0.1 0 0.1 0.2 0.3) ymtick(-0.1 0 0.1 0.2 0.3)   ///
>   ytitle("HDDS", size(small)) levels(95) 
{res}{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
grey not found in class
color,  default attributes used)
{p_end}
{res}{txt}
{com}. 
. graph save "Figure_3c_Sources.gph", replace
{res}{txt}(file Figure_3c_Sources.gph saved)

{com}. restore 
{txt}
{com}. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *          Figure 4_Impact of Production Diversity by regional levels          *
. ********************************************************************************
. preserve
{txt}
{com}. drop if sum_vill<=1|sum_vill==.
{txt}(24,163 observations deleted)

{com}. 
. drop pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. egen pdd9_mean=mean(pdd9), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_vill=mean(pdd9_vill), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_town=mean(pdd9_town), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_dist=mean(pdd9_dist), by(HHID_panel)
{txt}
{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. eststo clear
{txt}
{com}. *Whole Sample
. gen pdd9_whole=pdd9
{txt}
{com}. xtreg hdd9  pdd9_whole   $xlist  pdd9_mean i.country i.year  , cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    65,579
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,229

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0298                                         {txt}min = {res}         1
{txt}     between = {res}0.3642                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2843                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 20480.98
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_whole {c |}{col 18}{res}{space 2} .1049413{col 30}{space 2} .0059733{col 41}{space 1}   17.57{col 50}{space 3}0.000{col 58}{space 4} .0932338{col 71}{space 3} .1166487
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.007599{col 30}{space 2} .0024818{col 41}{space 1}   -3.06{col 50}{space 3}0.002{col 58}{space 4}-.0124632{col 71}{space 3}-.0027349
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0471026{col 30}{space 2} .0276186{col 41}{space 1}    1.71{col 50}{space 3}0.088{col 58}{space 4}-.0070288{col 71}{space 3}  .101234
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0002698{col 30}{space 2}  .000465{col 41}{space 1}    0.58{col 50}{space 3}0.562{col 58}{space 4}-.0006416{col 71}{space 3} .0011812
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0699344{col 30}{space 2} .0169506{col 41}{space 1}    4.13{col 50}{space 3}0.000{col 58}{space 4} .0367118{col 71}{space 3} .1031569
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3054264{col 30}{space 2} .0147831{col 41}{space 1}   20.66{col 50}{space 3}0.000{col 58}{space 4}  .276452{col 71}{space 3} .3344008
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1195563{col 30}{space 2} .0293841{col 41}{space 1}    4.07{col 50}{space 3}0.000{col 58}{space 4} .0619646{col 71}{space 3} .1771481
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1690675{col 30}{space 2} .0192528{col 41}{space 1}    8.78{col 50}{space 3}0.000{col 58}{space 4} .1313326{col 71}{space 3} .2068024
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1509031{col 30}{space 2} .0227388{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .1063359{col 71}{space 3} .1954703
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .127408{col 30}{space 2} .0198305{col 41}{space 1}    6.42{col 50}{space 3}0.000{col 58}{space 4}  .088541{col 71}{space 3} .1662751
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2082576{col 30}{space 2}  .018241{col 41}{space 1}   11.42{col 50}{space 3}0.000{col 58}{space 4}  .172506{col 71}{space 3} .2440092
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.069053{col 30}{space 2} .0142275{col 41}{space 1}   -4.85{col 50}{space 3}0.000{col 58}{space 4}-.0969385{col 71}{space 3}-.0411676
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0010025{col 30}{space 2} .0011243{col 41}{space 1}   -0.89{col 50}{space 3}0.373{col 58}{space 4} -.003206{col 71}{space 3}  .001201
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1214571{col 30}{space 2} .0162303{col 41}{space 1}    7.48{col 50}{space 3}0.000{col 58}{space 4} .0896462{col 71}{space 3} .1532679
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .041509{col 30}{space 2} .0397187{col 41}{space 1}    1.05{col 50}{space 3}0.296{col 58}{space 4}-.0363382{col 71}{space 3} .1193562
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .570139{col 30}{space 2} .0280369{col 41}{space 1}   20.34{col 50}{space 3}0.000{col 58}{space 4} .5151878{col 71}{space 3} .6250902
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7014075{col 30}{space 2}  .031095{col 41}{space 1}   22.56{col 50}{space 3}0.000{col 58}{space 4} .6404625{col 71}{space 3} .7623526
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2016277{col 30}{space 2} .0294769{col 41}{space 1}    6.84{col 50}{space 3}0.000{col 58}{space 4} .1438539{col 71}{space 3} .2594014
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1698562{col 30}{space 2} .0255933{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .1196942{col 71}{space 3} .2200183
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0224813{col 30}{space 2} .0079096{col 41}{space 1}   -2.84{col 50}{space 3}0.004{col 58}{space 4}-.0379839{col 71}{space 3}-.0069786
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3748805{col 30}{space 2} .0320616{col 41}{space 1}  -11.69{col 50}{space 3}0.000{col 58}{space 4}-.4377201{col 71}{space 3} -.312041
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.505376{col 30}{space 2} .0312475{col 41}{space 1}  -48.18{col 50}{space 3}0.000{col 58}{space 4} -1.56662{col 71}{space 3}-1.444132
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4763147{col 30}{space 2} .0314446{col 41}{space 1}  -15.15{col 50}{space 3}0.000{col 58}{space 4} -.537945{col 71}{space 3}-.4146844
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.2621974{col 30}{space 2} .0313699{col 41}{space 1}   -8.36{col 50}{space 3}0.000{col 58}{space 4}-.3236813{col 71}{space 3}-.2007135
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .4473528{col 30}{space 2} .0408327{col 41}{space 1}   10.96{col 50}{space 3}0.000{col 58}{space 4} .3673221{col 71}{space 3} .5273835
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2119596{col 30}{space 2} .0460785{col 41}{space 1}   -4.60{col 50}{space 3}0.000{col 58}{space 4}-.3022718{col 71}{space 3}-.1216475
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0370795{col 30}{space 2} .0349394{col 41}{space 1}    1.06{col 50}{space 3}0.289{col 58}{space 4}-.0314005{col 71}{space 3} .1055595
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0917951{col 30}{space 2} .0387084{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0159281{col 71}{space 3} .1676621
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0461867{col 30}{space 2} .0354764{col 41}{space 1}    1.30{col 50}{space 3}0.193{col 58}{space 4}-.0233458{col 71}{space 3} .1157192
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1282528{col 30}{space 2} .0389711{col 41}{space 1}    3.29{col 50}{space 3}0.001{col 58}{space 4} .0518708{col 71}{space 3} .2046348
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0501073{col 30}{space 2} .0392824{col 41}{space 1}   -1.28{col 50}{space 3}0.202{col 58}{space 4}-.1270995{col 71}{space 3} .0268849
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1921556{col 30}{space 2} .0378514{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4} .1179681{col 71}{space 3}  .266343
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1711942{col 30}{space 2} .0586205{col 41}{space 1}   -2.92{col 50}{space 3}0.003{col 58}{space 4}-.2860882{col 71}{space 3}-.0563002
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4721261{col 30}{space 2} .0399222{col 41}{space 1}   11.83{col 50}{space 3}0.000{col 58}{space 4}   .39388{col 71}{space 3} .5503723
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0124794{col 30}{space 2} .0388179{col 41}{space 1}    0.32{col 50}{space 3}0.748{col 58}{space 4}-.0636023{col 71}{space 3} .0885612
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.442334{col 30}{space 2} .0534638{col 41}{space 1}   83.09{col 50}{space 3}0.000{col 58}{space 4} 4.337547{col 71}{space 3} 4.547122
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80391868
         {txt}sigma_e {c |} {res} 1.2322889
             {txt}rho {c |} {res} .29853977{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. drop pdd9_whole
{txt}
{com}. gen pdd9_whole= pdd9_vill
{txt}
{com}. xtreg hdd9  pdd9_whole sum_vill  $xlist  pdd9_mean_vill i.country i.year  , cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    65,579
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,229

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0219                                         {txt}min = {res}         1
{txt}     between = {res}0.3733                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2881                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 20864.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_whole {c |}{col 18}{res}{space 2} .0437778{col 30}{space 2} .0071365{col 41}{space 1}    6.13{col 50}{space 3}0.000{col 58}{space 4} .0297906{col 71}{space 3}  .057765
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0494106{col 30}{space 2} .0024984{col 41}{space 1}  -19.78{col 50}{space 3}0.000{col 58}{space 4}-.0543075{col 71}{space 3}-.0445138
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0037478{col 30}{space 2} .0024298{col 41}{space 1}    1.54{col 50}{space 3}0.123{col 58}{space 4}-.0010145{col 71}{space 3} .0085101
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0463807{col 30}{space 2} .0276535{col 41}{space 1}    1.68{col 50}{space 3}0.094{col 58}{space 4}-.0078191{col 71}{space 3} .1005805
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0000317{col 30}{space 2} .0004617{col 41}{space 1}    0.07{col 50}{space 3}0.945{col 58}{space 4}-.0008732{col 71}{space 3} .0009366
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0347232{col 30}{space 2} .0168878{col 41}{space 1}    2.06{col 50}{space 3}0.040{col 58}{space 4} .0016238{col 71}{space 3} .0678227
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2981026{col 30}{space 2} .0147565{col 41}{space 1}   20.20{col 50}{space 3}0.000{col 58}{space 4} .2691804{col 71}{space 3} .3270247
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1241965{col 30}{space 2} .0294339{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4} .0665072{col 71}{space 3} .1818858
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1724967{col 30}{space 2} .0193431{col 41}{space 1}    8.92{col 50}{space 3}0.000{col 58}{space 4}  .134585{col 71}{space 3} .2104085
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1425662{col 30}{space 2} .0228219{col 41}{space 1}    6.25{col 50}{space 3}0.000{col 58}{space 4}  .097836{col 71}{space 3} .1872964
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1273375{col 30}{space 2} .0199251{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .0882849{col 71}{space 3}   .16639
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2146016{col 30}{space 2} .0183202{col 41}{space 1}   11.71{col 50}{space 3}0.000{col 58}{space 4} .1786947{col 71}{space 3} .2505085
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0347813{col 30}{space 2} .0142726{col 41}{space 1}   -2.44{col 50}{space 3}0.015{col 58}{space 4}-.0627551{col 71}{space 3}-.0068074
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0006481{col 30}{space 2} .0010929{col 41}{space 1}    0.59{col 50}{space 3}0.553{col 58}{space 4}-.0014939{col 71}{space 3} .0027901
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1643842{col 30}{space 2} .0159668{col 41}{space 1}   10.30{col 50}{space 3}0.000{col 58}{space 4} .1330899{col 71}{space 3} .1956786
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0440769{col 30}{space 2} .0394896{col 41}{space 1}    1.12{col 50}{space 3}0.264{col 58}{space 4}-.0333214{col 71}{space 3} .1214752
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5268787{col 30}{space 2} .0280367{col 41}{space 1}   18.79{col 50}{space 3}0.000{col 58}{space 4} .4719278{col 71}{space 3} .5818295
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6096075{col 30}{space 2} .0309691{col 41}{space 1}   19.68{col 50}{space 3}0.000{col 58}{space 4} .5489091{col 71}{space 3} .6703059
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1222808{col 30}{space 2} .0294909{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4} .0644797{col 71}{space 3}  .180082
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1239314{col 30}{space 2} .0255049{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4} .0739427{col 71}{space 3} .1739201
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0843952{col 30}{space 2} .0090772{col 41}{space 1}    9.30{col 50}{space 3}0.000{col 58}{space 4} .0666042{col 71}{space 3} .1021862
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.5864976{col 30}{space 2} .0332015{col 41}{space 1}  -17.66{col 50}{space 3}0.000{col 58}{space 4}-.6515714{col 71}{space 3}-.5214239
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.798805{col 30}{space 2} .0340658{col 41}{space 1}  -52.80{col 50}{space 3}0.000{col 58}{space 4}-1.865573{col 71}{space 3}-1.732037
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.7861785{col 30}{space 2} .0345986{col 41}{space 1}  -22.72{col 50}{space 3}0.000{col 58}{space 4}-.8539905{col 71}{space 3}-.7183664
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.6806499{col 30}{space 2}  .037041{col 41}{space 1}  -18.38{col 50}{space 3}0.000{col 58}{space 4} -.753249{col 71}{space 3}-.6080508
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .2354971{col 30}{space 2} .0420555{col 41}{space 1}    5.60{col 50}{space 3}0.000{col 58}{space 4} .1530699{col 71}{space 3} .3179244
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2273892{col 30}{space 2} .0463509{col 41}{space 1}   -4.91{col 50}{space 3}0.000{col 58}{space 4}-.3182353{col 71}{space 3} -.136543
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0683135{col 30}{space 2} .0353012{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-.0008756{col 71}{space 3} .1375026
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0897435{col 30}{space 2} .0389891{col 41}{space 1}    2.30{col 50}{space 3}0.021{col 58}{space 4} .0133264{col 71}{space 3} .1661606
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0606066{col 30}{space 2} .0358046{col 41}{space 1}    1.69{col 50}{space 3}0.091{col 58}{space 4}-.0095691{col 71}{space 3} .1307823
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1544148{col 30}{space 2} .0394444{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4} .0771051{col 71}{space 3} .2317245
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0372272{col 30}{space 2} .0397642{col 41}{space 1}   -0.94{col 50}{space 3}0.349{col 58}{space 4}-.1151636{col 71}{space 3} .0407091
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2217062{col 30}{space 2} .0382131{col 41}{space 1}    5.80{col 50}{space 3}0.000{col 58}{space 4} .1468099{col 71}{space 3} .2966025
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2184384{col 30}{space 2} .0587745{col 41}{space 1}   -3.72{col 50}{space 3}0.000{col 58}{space 4}-.3336343{col 71}{space 3}-.1032425
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4901667{col 30}{space 2}  .040204{col 41}{space 1}   12.19{col 50}{space 3}0.000{col 58}{space 4} .4113682{col 71}{space 3} .5689651
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0207715{col 30}{space 2} .0392038{col 41}{space 1}    0.53{col 50}{space 3}0.596{col 58}{space 4}-.0560665{col 71}{space 3} .0976095
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.696564{col 30}{space 2} .0607587{col 41}{space 1}   77.30{col 50}{space 3}0.000{col 58}{space 4}  4.57748{col 71}{space 3} 4.815649
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78888658
         {txt}sigma_e {c |} {res} 1.2371012
             {txt}rho {c |} {res} .28909012{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. 
. drop pdd9_whole
{txt}
{com}. gen pdd9_whole= pdd9_town
{txt}
{com}. xtreg hdd9  pdd9_whole sum_town  $xlist  pdd9_mean_town i.country i.year, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    65,579
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,229

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0230                                         {txt}min = {res}         1
{txt}     between = {res}0.3659                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2832                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 20269.46
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_whole {c |}{col 18}{res}{space 2}  .024555{col 30}{space 2} .0073425{col 41}{space 1}    3.34{col 50}{space 3}0.001{col 58}{space 4}  .010164{col 71}{space 3}  .038946
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0017515{col 30}{space 2} .0002209{col 41}{space 1}   -7.93{col 50}{space 3}0.000{col 58}{space 4}-.0021845{col 71}{space 3}-.0013184
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0016164{col 30}{space 2} .0024382{col 41}{space 1}    0.66{col 50}{space 3}0.507{col 58}{space 4}-.0031624{col 71}{space 3} .0063953
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0353018{col 30}{space 2} .0277299{col 41}{space 1}    1.27{col 50}{space 3}0.203{col 58}{space 4}-.0190478{col 71}{space 3} .0896514
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0005458{col 30}{space 2} .0004634{col 41}{space 1}    1.18{col 50}{space 3}0.239{col 58}{space 4}-.0003625{col 71}{space 3} .0014542
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0476093{col 30}{space 2} .0169331{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4}  .014421{col 71}{space 3} .0807975
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3060074{col 30}{space 2} .0148137{col 41}{space 1}   20.66{col 50}{space 3}0.000{col 58}{space 4} .2769731{col 71}{space 3} .3350417
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .126764{col 30}{space 2} .0294804{col 41}{space 1}    4.30{col 50}{space 3}0.000{col 58}{space 4} .0689836{col 71}{space 3} .1845444
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1769806{col 30}{space 2}  .019319{col 41}{space 1}    9.16{col 50}{space 3}0.000{col 58}{space 4} .1391162{col 71}{space 3} .2148451
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1497898{col 30}{space 2} .0228068{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .1050893{col 71}{space 3} .1944903
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1281352{col 30}{space 2} .0199232{col 41}{space 1}    6.43{col 50}{space 3}0.000{col 58}{space 4} .0890866{col 71}{space 3} .1671839
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2177776{col 30}{space 2}  .018309{col 41}{space 1}   11.89{col 50}{space 3}0.000{col 58}{space 4} .1818927{col 71}{space 3} .2536625
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.052856{col 30}{space 2} .0142538{col 41}{space 1}   -3.71{col 50}{space 3}0.000{col 58}{space 4}-.0807929{col 71}{space 3} -.024919
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0001995{col 30}{space 2} .0011021{col 41}{space 1}    0.18{col 50}{space 3}0.856{col 58}{space 4}-.0019607{col 71}{space 3} .0023596
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .155978{col 30}{space 2} .0160538{col 41}{space 1}    9.72{col 50}{space 3}0.000{col 58}{space 4} .1245132{col 71}{space 3} .1874428
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0292711{col 30}{space 2} .0396366{col 41}{space 1}    0.74{col 50}{space 3}0.460{col 58}{space 4}-.0484152{col 71}{space 3} .1069573
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5539139{col 30}{space 2}  .028099{col 41}{space 1}   19.71{col 50}{space 3}0.000{col 58}{space 4} .4988409{col 71}{space 3} .6089869
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6845201{col 30}{space 2}  .030759{col 41}{space 1}   22.25{col 50}{space 3}0.000{col 58}{space 4} .6242335{col 71}{space 3} .7448067
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1703215{col 30}{space 2} .0294106{col 41}{space 1}    5.79{col 50}{space 3}0.000{col 58}{space 4} .1126778{col 71}{space 3} .2279652
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .148127{col 30}{space 2} .0255564{col 41}{space 1}    5.80{col 50}{space 3}0.000{col 58}{space 4} .0980373{col 71}{space 3} .1982167
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0831302{col 30}{space 2} .0094012{col 41}{space 1}    8.84{col 50}{space 3}0.000{col 58}{space 4} .0647041{col 71}{space 3} .1015563
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3504199{col 30}{space 2} .0346934{col 41}{space 1}  -10.10{col 50}{space 3}0.000{col 58}{space 4}-.4184177{col 71}{space 3}-.2824222
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.569396{col 30}{space 2} .0336568{col 41}{space 1}  -46.63{col 50}{space 3}0.000{col 58}{space 4}-1.635362{col 71}{space 3} -1.50343
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.5278385{col 30}{space 2} .0340999{col 41}{space 1}  -15.48{col 50}{space 3}0.000{col 58}{space 4}-.5946731{col 71}{space 3}-.4610039
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3160157{col 30}{space 2} .0342103{col 41}{space 1}   -9.24{col 50}{space 3}0.000{col 58}{space 4}-.3830666{col 71}{space 3}-.2489648
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .3591224{col 30}{space 2} .0432505{col 41}{space 1}    8.30{col 50}{space 3}0.000{col 58}{space 4} .2743529{col 71}{space 3} .4438918
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2385168{col 30}{space 2} .0463843{col 41}{space 1}   -5.14{col 50}{space 3}0.000{col 58}{space 4}-.3294284{col 71}{space 3}-.1476052
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0095335{col 30}{space 2} .0351702{col 41}{space 1}    0.27{col 50}{space 3}0.786{col 58}{space 4}-.0593989{col 71}{space 3} .0784659
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0300469{col 30}{space 2} .0388651{col 41}{space 1}    0.77{col 50}{space 3}0.439{col 58}{space 4}-.0461272{col 71}{space 3} .1062211
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0126483{col 30}{space 2} .0357017{col 41}{space 1}    0.35{col 50}{space 3}0.723{col 58}{space 4}-.0573257{col 71}{space 3} .0826224
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1110819{col 30}{space 2}  .039333{col 41}{space 1}    2.82{col 50}{space 3}0.005{col 58}{space 4} .0339907{col 71}{space 3}  .188173
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0936021{col 30}{space 2} .0395287{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4} -.171077{col 71}{space 3}-.0161273
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1703518{col 30}{space 2} .0381182{col 41}{space 1}    4.47{col 50}{space 3}0.000{col 58}{space 4} .0956415{col 71}{space 3} .2450621
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2216465{col 30}{space 2} .0587194{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.3367344{col 71}{space 3}-.1065586
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4205357{col 30}{space 2} .0401217{col 41}{space 1}   10.48{col 50}{space 3}0.000{col 58}{space 4} .3418987{col 71}{space 3} .4991727
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0170279{col 30}{space 2}  .039106{col 41}{space 1}   -0.44{col 50}{space 3}0.663{col 58}{space 4}-.0936744{col 71}{space 3} .0596185
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.113824{col 30}{space 2} .0622117{col 41}{space 1}   66.13{col 50}{space 3}0.000{col 58}{space 4} 3.991891{col 71}{space 3} 4.235757
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .79816042
         {txt}sigma_e {c |} {res} 1.2370778
             {txt}rho {c |} {res}  .2939253{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. drop pdd9_whole
{txt}
{com}. gen pdd9_whole= pdd9_dist
{txt}
{com}. xtreg hdd9  pdd9_whole sum_dist  $xlist  pdd9_mean_dist i.country i.year, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    65,579
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,229

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0230                                         {txt}min = {res}         1
{txt}     between = {res}0.3626                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2804                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 19980.47
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_whole {c |}{col 18}{res}{space 2} .0276536{col 30}{space 2} .0089374{col 41}{space 1}    3.09{col 50}{space 3}0.002{col 58}{space 4} .0101366{col 71}{space 3} .0451706
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0012017{col 30}{space 2} .0001735{col 41}{space 1}   -6.92{col 50}{space 3}0.000{col 58}{space 4}-.0015418{col 71}{space 3}-.0008616
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0018877{col 30}{space 2} .0024456{col 41}{space 1}    0.77{col 50}{space 3}0.440{col 58}{space 4}-.0029057{col 71}{space 3} .0066811
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0391904{col 30}{space 2} .0277685{col 41}{space 1}    1.41{col 50}{space 3}0.158{col 58}{space 4}-.0152349{col 71}{space 3} .0936157
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .000823{col 30}{space 2} .0004648{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4} -.000088{col 71}{space 3} .0017339
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0489449{col 30}{space 2}  .016976{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0156726{col 71}{space 3} .0822172
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3077784{col 30}{space 2}  .014833{col 41}{space 1}   20.75{col 50}{space 3}0.000{col 58}{space 4} .2787062{col 71}{space 3} .3368506
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1258278{col 30}{space 2} .0294529{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .0681013{col 71}{space 3} .1835544
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1764518{col 30}{space 2} .0193197{col 41}{space 1}    9.13{col 50}{space 3}0.000{col 58}{space 4}  .138586{col 71}{space 3} .2143177
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1482962{col 30}{space 2} .0228056{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4}  .103598{col 71}{space 3} .1929943
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1285032{col 30}{space 2} .0199302{col 41}{space 1}    6.45{col 50}{space 3}0.000{col 58}{space 4} .0894408{col 71}{space 3} .1675656
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .216961{col 30}{space 2} .0183071{col 41}{space 1}   11.85{col 50}{space 3}0.000{col 58}{space 4} .1810798{col 71}{space 3} .2528422
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0497091{col 30}{space 2} .0142743{col 41}{space 1}   -3.48{col 50}{space 3}0.000{col 58}{space 4}-.0776863{col 71}{space 3}-.0217319
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}   .00056{col 30}{space 2} .0011008{col 41}{space 1}    0.51{col 50}{space 3}0.611{col 58}{space 4}-.0015976{col 71}{space 3} .0027176
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1757759{col 30}{space 2} .0160339{col 41}{space 1}   10.96{col 50}{space 3}0.000{col 58}{space 4} .1443501{col 71}{space 3} .2072017
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0480994{col 30}{space 2} .0396842{col 41}{space 1}    1.21{col 50}{space 3}0.225{col 58}{space 4}-.0296803{col 71}{space 3} .1258791
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5526723{col 30}{space 2} .0281432{col 41}{space 1}   19.64{col 50}{space 3}0.000{col 58}{space 4} .4975127{col 71}{space 3} .6078319
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6527534{col 30}{space 2} .0307272{col 41}{space 1}   21.24{col 50}{space 3}0.000{col 58}{space 4} .5925291{col 71}{space 3} .7129776
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1543829{col 30}{space 2} .0294354{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .0966906{col 71}{space 3} .2120752
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .130753{col 30}{space 2} .0256285{col 41}{space 1}    5.10{col 50}{space 3}0.000{col 58}{space 4} .0805221{col 71}{space 3} .1809838
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0690881{col 30}{space 2} .0116031{col 41}{space 1}    5.95{col 50}{space 3}0.000{col 58}{space 4} .0463464{col 71}{space 3} .0918299
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.445292{col 30}{space 2}  .033389{col 41}{space 1}  -13.34{col 50}{space 3}0.000{col 58}{space 4}-.5107333{col 71}{space 3}-.3798507
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.544517{col 30}{space 2} .0374335{col 41}{space 1}  -41.26{col 50}{space 3}0.000{col 58}{space 4}-1.617886{col 71}{space 3}-1.471149
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.5596247{col 30}{space 2} .0371388{col 41}{space 1}  -15.07{col 50}{space 3}0.000{col 58}{space 4}-.6324154{col 71}{space 3} -.486834
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3500165{col 30}{space 2} .0372157{col 41}{space 1}   -9.41{col 50}{space 3}0.000{col 58}{space 4}-.4229578{col 71}{space 3}-.2770751
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .3556371{col 30}{space 2} .0442729{col 41}{space 1}    8.03{col 50}{space 3}0.000{col 58}{space 4} .2688639{col 71}{space 3} .4424103
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2446711{col 30}{space 2} .0463497{col 41}{space 1}   -5.28{col 50}{space 3}0.000{col 58}{space 4}-.3355148{col 71}{space 3}-.1538274
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0149716{col 30}{space 2} .0351828{col 41}{space 1}    0.43{col 50}{space 3}0.670{col 58}{space 4}-.0539853{col 71}{space 3} .0839286
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0405378{col 30}{space 2} .0388588{col 41}{space 1}    1.04{col 50}{space 3}0.297{col 58}{space 4} -.035624{col 71}{space 3} .1166996
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0198027{col 30}{space 2} .0357446{col 41}{space 1}    0.55{col 50}{space 3}0.580{col 58}{space 4}-.0502555{col 71}{space 3} .0898608
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1188008{col 30}{space 2} .0393772{col 41}{space 1}    3.02{col 50}{space 3}0.003{col 58}{space 4} .0416229{col 71}{space 3} .1959787
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0940588{col 30}{space 2} .0394564{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4} -.171392{col 71}{space 3}-.0167256
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1783709{col 30}{space 2} .0381119{col 41}{space 1}    4.68{col 50}{space 3}0.000{col 58}{space 4}  .103673{col 71}{space 3} .2530689
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2198642{col 30}{space 2} .0586947{col 41}{space 1}   -3.75{col 50}{space 3}0.000{col 58}{space 4}-.3349036{col 71}{space 3}-.1048247
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4290466{col 30}{space 2} .0403644{col 41}{space 1}   10.63{col 50}{space 3}0.000{col 58}{space 4} .3499339{col 71}{space 3} .5081593
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0101468{col 30}{space 2} .0390861{col 41}{space 1}   -0.26{col 50}{space 3}0.795{col 58}{space 4}-.0867541{col 71}{space 3} .0664606
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.118053{col 30}{space 2} .0719612{col 41}{space 1}   57.23{col 50}{space 3}0.000{col 58}{space 4} 3.977012{col 71}{space 3} 4.259095
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80300386
         {txt}sigma_e {c |} {res}  1.237148
             {txt}rho {c |} {res}   .296419{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. 
. 
. 
. 
. *Ethiopia
. gen pdd9_3=pdd9
{txt}
{com}. xtreg hdd9  pdd9_3   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,410
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,555

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0224                                         {txt}min = {res}         1
{txt}     between = {res}0.3316                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2218                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  2458.70
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_3 {c |}{col 18}{res}{space 2} .0539287{col 30}{space 2} .0110239{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4} .0323223{col 71}{space 3} .0755351
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0309614{col 30}{space 2} .0072656{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .0167211{col 71}{space 3} .0452018
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0466737{col 30}{space 2} .0571691{col 41}{space 1}   -0.82{col 50}{space 3}0.414{col 58}{space 4} -.158723{col 71}{space 3} .0653757
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0038514{col 30}{space 2} .0009949{col 41}{space 1}   -3.87{col 50}{space 3}0.000{col 58}{space 4}-.0058013{col 71}{space 3}-.0019014
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0028412{col 30}{space 2}  .036026{col 41}{space 1}   -0.08{col 50}{space 3}0.937{col 58}{space 4}-.0734508{col 71}{space 3} .0677685
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}   .38516{col 30}{space 2} .0312284{col 41}{space 1}   12.33{col 50}{space 3}0.000{col 58}{space 4} .3239536{col 71}{space 3} .4463665
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2271194{col 30}{space 2} .1577828{col 41}{space 1}   -1.44{col 50}{space 3}0.150{col 58}{space 4}-.5363681{col 71}{space 3} .0821293
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1805965{col 30}{space 2} .0377677{col 41}{space 1}    4.78{col 50}{space 3}0.000{col 58}{space 4} .1065732{col 71}{space 3} .2546197
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1561482{col 30}{space 2} .0461328{col 41}{space 1}    3.38{col 50}{space 3}0.001{col 58}{space 4} .0657295{col 71}{space 3} .2465669
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0873407{col 30}{space 2} .0633302{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0367843{col 71}{space 3} .2114657
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2272176{col 30}{space 2} .0498917{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .1294317{col 71}{space 3} .3250035
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  -.14566{col 30}{space 2} .0293752{col 41}{space 1}   -4.96{col 50}{space 3}0.000{col 58}{space 4}-.2032344{col 71}{space 3}-.0880857
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0076979{col 30}{space 2} .0035577{col 41}{space 1}    2.16{col 50}{space 3}0.030{col 58}{space 4} .0007249{col 71}{space 3} .0146709
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2120122{col 30}{space 2} .0311265{col 41}{space 1}    6.81{col 50}{space 3}0.000{col 58}{space 4} .1510054{col 71}{space 3} .2730191
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.059095{col 30}{space 2} .2656293{col 41}{space 1}    3.99{col 50}{space 3}0.000{col 58}{space 4} .5384717{col 71}{space 3} 1.579719
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4714012{col 30}{space 2} .0570747{col 41}{space 1}    8.26{col 50}{space 3}0.000{col 58}{space 4} .3595368{col 71}{space 3} .5832656
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5146638{col 30}{space 2} .0678677{col 41}{space 1}    7.58{col 50}{space 3}0.000{col 58}{space 4} .3816456{col 71}{space 3}  .647682
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4982624{col 30}{space 2} .0977845{col 41}{space 1}    5.10{col 50}{space 3}0.000{col 58}{space 4} .3066083{col 71}{space 3} .6899165
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0978044{col 30}{space 2} .0635014{col 41}{space 1}    1.54{col 50}{space 3}0.124{col 58}{space 4}-.0266561{col 71}{space 3} .2222648
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0492839{col 30}{space 2} .0148333{col 41}{space 1}    3.32{col 50}{space 3}0.001{col 58}{space 4} .0202111{col 71}{space 3} .0783567
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1489418{col 30}{space 2} .0221739{col 41}{space 1}   -6.72{col 50}{space 3}0.000{col 58}{space 4}-.1924018{col 71}{space 3}-.1054817
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.138044{col 30}{space 2}  .071355{col 41}{space 1}   43.98{col 50}{space 3}0.000{col 58}{space 4} 2.998191{col 71}{space 3} 3.277897
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7322402
         {txt}sigma_e {c |} {res} 1.0763181
             {txt}rho {c |} {res} .31639574{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est11
{txt}
{com}. 
. drop pdd9_3
{txt}
{com}. gen pdd9_3= pdd9_vill
{txt}
{com}. xtreg hdd9  pdd9_3 sum_vill  $xlist  pdd9_mean_vill $year_ETHIOPIA if country==3, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,410
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,555

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0188                                         {txt}min = {res}         1
{txt}     between = {res}0.3385                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2264                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2542.72
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_3 {c |}{col 18}{res}{space 2} .0520459{col 30}{space 2} .0150217{col 41}{space 1}    3.46{col 50}{space 3}0.001{col 58}{space 4} .0226039{col 71}{space 3} .0814878
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0486224{col 30}{space 2} .0079267{col 41}{space 1}   -6.13{col 50}{space 3}0.000{col 58}{space 4}-.0641584{col 71}{space 3}-.0330863
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0522133{col 30}{space 2} .0069888{col 41}{space 1}    7.47{col 50}{space 3}0.000{col 58}{space 4} .0385155{col 71}{space 3}  .065911
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0536411{col 30}{space 2} .0571637{col 41}{space 1}   -0.94{col 50}{space 3}0.348{col 58}{space 4}-.1656799{col 71}{space 3} .0583978
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0033175{col 30}{space 2} .0009874{col 41}{space 1}   -3.36{col 50}{space 3}0.001{col 58}{space 4}-.0052527{col 71}{space 3}-.0013823
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0521864{col 30}{space 2} .0357111{col 41}{space 1}   -1.46{col 50}{space 3}0.144{col 58}{space 4}-.1221787{col 71}{space 3}  .017806
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3750429{col 30}{space 2} .0312713{col 41}{space 1}   11.99{col 50}{space 3}0.000{col 58}{space 4} .3137523{col 71}{space 3} .4363335
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2125058{col 30}{space 2} .1565102{col 41}{space 1}   -1.36{col 50}{space 3}0.175{col 58}{space 4}-.5192602{col 71}{space 3} .0942486
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .184056{col 30}{space 2} .0378492{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4}  .109873{col 71}{space 3}  .258239
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1634309{col 30}{space 2}  .046265{col 41}{space 1}    3.53{col 50}{space 3}0.000{col 58}{space 4} .0727532{col 71}{space 3} .2541086
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0764253{col 30}{space 2} .0630848{col 41}{space 1}    1.21{col 50}{space 3}0.226{col 58}{space 4}-.0472185{col 71}{space 3} .2000692
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2241372{col 30}{space 2} .0499909{col 41}{space 1}    4.48{col 50}{space 3}0.000{col 58}{space 4} .1261568{col 71}{space 3} .3221175
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1103295{col 30}{space 2} .0295293{col 41}{space 1}   -3.74{col 50}{space 3}0.000{col 58}{space 4}-.1682059{col 71}{space 3}-.0524532
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0140295{col 30}{space 2} .0036486{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4} .0068784{col 71}{space 3} .0211807
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2533167{col 30}{space 2} .0308971{col 41}{space 1}    8.20{col 50}{space 3}0.000{col 58}{space 4} .1927595{col 71}{space 3} .3138739
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.024552{col 30}{space 2} .2624628{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .5101349{col 71}{space 3}  1.53897
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4756492{col 30}{space 2} .0569103{col 41}{space 1}    8.36{col 50}{space 3}0.000{col 58}{space 4} .3641071{col 71}{space 3} .5871912
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3728838{col 30}{space 2} .0691018{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .2374467{col 71}{space 3} .5083209
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4263647{col 30}{space 2} .0970235{col 41}{space 1}    4.39{col 50}{space 3}0.000{col 58}{space 4} .2362022{col 71}{space 3} .6165272
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0567792{col 30}{space 2} .0634387{col 41}{space 1}    0.90{col 50}{space 3}0.371{col 58}{space 4}-.0675584{col 71}{space 3} .1811168
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0790103{col 30}{space 2} .0181094{col 41}{space 1}    4.36{col 50}{space 3}0.000{col 58}{space 4} .0435166{col 71}{space 3}  .114504
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1369882{col 30}{space 2} .0222928{col 41}{space 1}   -6.14{col 50}{space 3}0.000{col 58}{space 4}-.1806813{col 71}{space 3}-.0932952
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.066452{col 30}{space 2} .1031008{col 41}{space 1}   29.74{col 50}{space 3}0.000{col 58}{space 4} 2.864378{col 71}{space 3} 3.268526
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72872341
         {txt}sigma_e {c |} {res} 1.0778015
             {txt}rho {c |} {res} .31372346{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est21
{txt}
{com}. 
. 
. drop pdd9_3
{txt}
{com}. gen pdd9_3= pdd9_town
{txt}
{com}. xtreg hdd9  pdd9_3 sum_town  $xlist  pdd9_mean_town $year_ETHIOPIA if country==3, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,410
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,555

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0213                                         {txt}min = {res}         1
{txt}     between = {res}0.3343                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2247                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2483.50
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_3 {c |}{col 18}{res}{space 2} .0544296{col 30}{space 2} .0158992{col 41}{space 1}    3.42{col 50}{space 3}0.001{col 58}{space 4} .0232679{col 71}{space 3} .0855914
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0056712{col 30}{space 2} .0006116{col 41}{space 1}   -9.27{col 50}{space 3}0.000{col 58}{space 4}-.0068698{col 71}{space 3}-.0044726
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0503228{col 30}{space 2} .0070227{col 41}{space 1}    7.17{col 50}{space 3}0.000{col 58}{space 4} .0365585{col 71}{space 3}  .064087
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0624082{col 30}{space 2} .0573747{col 41}{space 1}   -1.09{col 50}{space 3}0.277{col 58}{space 4}-.1748605{col 71}{space 3} .0500442
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.003466{col 30}{space 2} .0009883{col 41}{space 1}   -3.51{col 50}{space 3}0.000{col 58}{space 4}-.0054031{col 71}{space 3}-.0015289
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0529192{col 30}{space 2} .0357638{col 41}{space 1}   -1.48{col 50}{space 3}0.139{col 58}{space 4}-.1230149{col 71}{space 3} .0171766
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3687682{col 30}{space 2} .0313347{col 41}{space 1}   11.77{col 50}{space 3}0.000{col 58}{space 4} .3073533{col 71}{space 3}  .430183
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2110038{col 30}{space 2} .1571486{col 41}{space 1}   -1.34{col 50}{space 3}0.179{col 58}{space 4}-.5190093{col 71}{space 3} .0970018
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1807972{col 30}{space 2} .0377411{col 41}{space 1}    4.79{col 50}{space 3}0.000{col 58}{space 4}  .106826{col 71}{space 3} .2547684
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1633286{col 30}{space 2} .0460337{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4} .0731041{col 71}{space 3} .2535531
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0782836{col 30}{space 2} .0632242{col 41}{space 1}    1.24{col 50}{space 3}0.216{col 58}{space 4}-.0456336{col 71}{space 3} .2022008
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2214184{col 30}{space 2} .0499538{col 41}{space 1}    4.43{col 50}{space 3}0.000{col 58}{space 4} .1235108{col 71}{space 3}  .319326
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1161477{col 30}{space 2} .0295255{col 41}{space 1}   -3.93{col 50}{space 3}0.000{col 58}{space 4}-.1740166{col 71}{space 3}-.0582788
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0123207{col 30}{space 2} .0035941{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4} .0052764{col 71}{space 3} .0193649
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2676345{col 30}{space 2} .0310055{col 41}{space 1}    8.63{col 50}{space 3}0.000{col 58}{space 4} .2068648{col 71}{space 3} .3284041
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9553488{col 30}{space 2}  .261049{col 41}{space 1}    3.66{col 50}{space 3}0.000{col 58}{space 4} .4437021{col 71}{space 3} 1.466996
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4631296{col 30}{space 2} .0568723{col 41}{space 1}    8.14{col 50}{space 3}0.000{col 58}{space 4} .3516619{col 71}{space 3} .5745973
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5184451{col 30}{space 2} .0670629{col 41}{space 1}    7.73{col 50}{space 3}0.000{col 58}{space 4} .3870043{col 71}{space 3} .6498858
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4502796{col 30}{space 2} .0971828{col 41}{space 1}    4.63{col 50}{space 3}0.000{col 58}{space 4} .2598049{col 71}{space 3} .6407543
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1009689{col 30}{space 2} .0634125{col 41}{space 1}    1.59{col 50}{space 3}0.111{col 58}{space 4}-.0233174{col 71}{space 3} .2252552
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0490843{col 30}{space 2} .0193443{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .0111703{col 71}{space 3} .0869984
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1373436{col 30}{space 2} .0220914{col 41}{space 1}   -6.22{col 50}{space 3}0.000{col 58}{space 4}-.1806421{col 71}{space 3}-.0940452
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  2.81016{col 30}{space 2}  .093887{col 41}{space 1}   29.93{col 50}{space 3}0.000{col 58}{space 4} 2.626145{col 71}{space 3} 2.994175
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .73031715
         {txt}sigma_e {c |} {res} 1.0776877
             {txt}rho {c |} {res} .31471049{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est31
{txt}
{com}. 
. 
. drop pdd9_3
{txt}
{com}. gen pdd9_3= pdd9_dist
{txt}
{com}. xtreg hdd9  pdd9_3 sum_dist  $xlist  pdd9_mean_dist $year_ETHIOPIA if country==3, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,410
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,555

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0208                                         {txt}min = {res}         1
{txt}     between = {res}0.3306                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2214                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2427.97
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_3 {c |}{col 18}{res}{space 2} .0582772{col 30}{space 2}   .01635{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .0262317{col 71}{space 3} .0903227
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0050642{col 30}{space 2} .0006027{col 41}{space 1}   -8.40{col 50}{space 3}0.000{col 58}{space 4}-.0062455{col 71}{space 3} -.003883
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0508188{col 30}{space 2} .0070343{col 41}{space 1}    7.22{col 50}{space 3}0.000{col 58}{space 4} .0370318{col 71}{space 3} .0646058
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0501728{col 30}{space 2} .0574816{col 41}{space 1}   -0.87{col 50}{space 3}0.383{col 58}{space 4}-.1628346{col 71}{space 3}  .062489
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0035228{col 30}{space 2} .0009921{col 41}{space 1}   -3.55{col 50}{space 3}0.000{col 58}{space 4}-.0054673{col 71}{space 3}-.0015783
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0568493{col 30}{space 2} .0358722{col 41}{space 1}   -1.58{col 50}{space 3}0.113{col 58}{space 4}-.1271576{col 71}{space 3} .0134589
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3706652{col 30}{space 2} .0314203{col 41}{space 1}   11.80{col 50}{space 3}0.000{col 58}{space 4} .3090826{col 71}{space 3} .4322478
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2144557{col 30}{space 2} .1576262{col 41}{space 1}   -1.36{col 50}{space 3}0.174{col 58}{space 4}-.5233974{col 71}{space 3}  .094486
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1805397{col 30}{space 2} .0377566{col 41}{space 1}    4.78{col 50}{space 3}0.000{col 58}{space 4}  .106538{col 71}{space 3} .2545413
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1631594{col 30}{space 2} .0460696{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} .0728647{col 71}{space 3} .2534541
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0772026{col 30}{space 2} .0632147{col 41}{space 1}    1.22{col 50}{space 3}0.222{col 58}{space 4}-.0466959{col 71}{space 3} .2011012
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2202839{col 30}{space 2} .0499724{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .1223398{col 71}{space 3} .3182281
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1216917{col 30}{space 2} .0295897{col 41}{space 1}   -4.11{col 50}{space 3}0.000{col 58}{space 4}-.1796864{col 71}{space 3} -.063697
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0130256{col 30}{space 2} .0036071{col 41}{space 1}    3.61{col 50}{space 3}0.000{col 58}{space 4} .0059558{col 71}{space 3} .0200954
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2958851{col 30}{space 2} .0308028{col 41}{space 1}    9.61{col 50}{space 3}0.000{col 58}{space 4} .2355127{col 71}{space 3} .3562575
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9844681{col 30}{space 2} .2615728{col 41}{space 1}    3.76{col 50}{space 3}0.000{col 58}{space 4} .4717949{col 71}{space 3} 1.497141
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4577851{col 30}{space 2} .0569903{col 41}{space 1}    8.03{col 50}{space 3}0.000{col 58}{space 4} .3460861{col 71}{space 3} .5694841
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4724606{col 30}{space 2} .0667995{col 41}{space 1}    7.07{col 50}{space 3}0.000{col 58}{space 4}  .341536{col 71}{space 3} .6033851
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4264689{col 30}{space 2} .0972725{col 41}{space 1}    4.38{col 50}{space 3}0.000{col 58}{space 4} .2358184{col 71}{space 3} .6171194
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0952955{col 30}{space 2} .0635327{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.0292264{col 71}{space 3} .2198173
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0205645{col 30}{space 2} .0199462{col 41}{space 1}    1.03{col 50}{space 3}0.303{col 58}{space 4}-.0185292{col 71}{space 3} .0596583
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1411127{col 30}{space 2} .0221299{col 41}{space 1}   -6.38{col 50}{space 3}0.000{col 58}{space 4}-.1844866{col 71}{space 3}-.0977388
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.954891{col 30}{space 2} .0957704{col 41}{space 1}   30.85{col 50}{space 3}0.000{col 58}{space 4} 2.767184{col 71}{space 3} 3.142597
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .73382677
         {txt}sigma_e {c |} {res} 1.0775436
             {txt}rho {c |} {res}  .3168399{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est41
{txt}
{com}. 
. 
. 
. 
. *Malawi
. gen pdd9_6=pdd9
{txt}
{com}. xtreg hdd9  pdd9_6   $xlist  pdd9_mean $year_MALAWI if country==6, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,626
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,571

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0317                                         {txt}min = {res}         1
{txt}     between = {res}0.3927                                         {txt}avg = {res}       2.9
{txt}     overall = {res}0.2800                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1538.67
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_6 {c |}{col 18}{res}{space 2} .1235523{col 30}{space 2} .0191692{col 41}{space 1}    6.45{col 50}{space 3}0.000{col 58}{space 4} .0859814{col 71}{space 3} .1611232
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0097393{col 30}{space 2} .0113092{col 41}{space 1}   -0.86{col 50}{space 3}0.389{col 58}{space 4}-.0319049{col 71}{space 3} .0124263
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.268054{col 30}{space 2} .1034015{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4}-.4707172{col 71}{space 3}-.0653908
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0023176{col 30}{space 2} .0017155{col 41}{space 1}   -1.35{col 50}{space 3}0.177{col 58}{space 4}-.0056799{col 71}{space 3} .0010447
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1132922{col 30}{space 2} .0597651{col 41}{space 1}   -1.90{col 50}{space 3}0.058{col 58}{space 4}-.2304297{col 71}{space 3} .0038453
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2955717{col 30}{space 2} .0581609{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4} .1815785{col 71}{space 3}  .409565
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2775657{col 30}{space 2} .1910768{col 41}{space 1}    1.45{col 50}{space 3}0.146{col 58}{space 4}-.0969379{col 71}{space 3} .6520694
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0970273{col 30}{space 2} .0693982{col 41}{space 1}    1.40{col 50}{space 3}0.162{col 58}{space 4}-.0389906{col 71}{space 3} .2330451
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2106928{col 30}{space 2}  .139234{col 41}{space 1}    1.51{col 50}{space 3}0.130{col 58}{space 4}-.0622008{col 71}{space 3} .4835864
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1454629{col 30}{space 2} .0805816{col 41}{space 1}    1.81{col 50}{space 3}0.071{col 58}{space 4}-.0124742{col 71}{space 3}    .3034
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2402563{col 30}{space 2} .0558992{col 41}{space 1}    4.30{col 50}{space 3}0.000{col 58}{space 4} .1306959{col 71}{space 3} .3498168
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1657882{col 30}{space 2} .0439083{col 41}{space 1}   -3.78{col 50}{space 3}0.000{col 58}{space 4}-.2518469{col 71}{space 3}-.0797296
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0339784{col 30}{space 2} .0318202{col 41}{space 1}    1.07{col 50}{space 3}0.286{col 58}{space 4}-.0283881{col 71}{space 3}  .096345
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .035854{col 30}{space 2} .0613702{col 41}{space 1}    0.58{col 50}{space 3}0.559{col 58}{space 4}-.0844294{col 71}{space 3} .1561374
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} -.001975{col 30}{space 2} .3236041{col 41}{space 1}   -0.01{col 50}{space 3}0.995{col 58}{space 4}-.6362274{col 71}{space 3} .6322774
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7479989{col 30}{space 2} .1079948{col 41}{space 1}    6.93{col 50}{space 3}0.000{col 58}{space 4}  .536333{col 71}{space 3} .9596648
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.009716{col 30}{space 2}  .176302{col 41}{space 1}    5.73{col 50}{space 3}0.000{col 58}{space 4} .6641703{col 71}{space 3} 1.355262
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4037854{col 30}{space 2} .1147723{col 41}{space 1}    3.52{col 50}{space 3}0.000{col 58}{space 4} .1788358{col 71}{space 3} .6287349
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3272637{col 30}{space 2}  .099458{col 41}{space 1}    3.29{col 50}{space 3}0.001{col 58}{space 4} .1323296{col 71}{space 3} .5221978
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0265623{col 30}{space 2} .0292927{col 41}{space 1}   -0.91{col 50}{space 3}0.365{col 58}{space 4} -.083975{col 71}{space 3} .0308504
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2427374{col 30}{space 2} .0535284{col 41}{space 1}    4.53{col 50}{space 3}0.000{col 58}{space 4} .1378238{col 71}{space 3} .3476511
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0938632{col 30}{space 2} .0494037{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0029662{col 71}{space 3} .1906927
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.889279{col 30}{space 2} .1436995{col 41}{space 1}   34.02{col 50}{space 3}0.000{col 58}{space 4} 4.607633{col 71}{space 3} 5.170925
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70023067
         {txt}sigma_e {c |} {res} 1.2834502
             {txt}rho {c |} {res} .22938364{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est12
{txt}
{com}. 
. drop pdd9_6
{txt}
{com}. gen pdd9_6= pdd9_vill
{txt}
{com}. xtreg hdd9  pdd9_6 sum_vill  $xlist  pdd9_mean_vill $year_MALAWI if country==6, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,626
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,571

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0210                                         {txt}min = {res}         1
{txt}     between = {res}0.3941                                         {txt}avg = {res}       2.9
{txt}     overall = {res}0.2774                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1544.49
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_6 {c |}{col 18}{res}{space 2} .0655642{col 30}{space 2} .0255957{col 41}{space 1}    2.56{col 50}{space 3}0.010{col 58}{space 4} .0153975{col 71}{space 3} .1157309
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0380229{col 30}{space 2} .0100863{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.0577917{col 71}{space 3}-.0182541
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0000461{col 30}{space 2}  .011206{col 41}{space 1}   -0.00{col 50}{space 3}0.997{col 58}{space 4}-.0220095{col 71}{space 3} .0219174
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2440043{col 30}{space 2} .1029867{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4}-.4458546{col 71}{space 3}-.0421541
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0019926{col 30}{space 2} .0017105{col 41}{space 1}   -1.16{col 50}{space 3}0.244{col 58}{space 4}-.0053451{col 71}{space 3}   .00136
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1026714{col 30}{space 2} .0599256{col 41}{space 1}   -1.71{col 50}{space 3}0.087{col 58}{space 4}-.2201233{col 71}{space 3} .0147806
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3069651{col 30}{space 2} .0584492{col 41}{space 1}    5.25{col 50}{space 3}0.000{col 58}{space 4} .1924067{col 71}{space 3} .4215235
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2474592{col 30}{space 2} .1917102{col 41}{space 1}    1.29{col 50}{space 3}0.197{col 58}{space 4}-.1282859{col 71}{space 3} .6232043
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1008257{col 30}{space 2} .0695221{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4} -.035435{col 71}{space 3} .2370865
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .189066{col 30}{space 2} .1408435{col 41}{space 1}    1.34{col 50}{space 3}0.179{col 58}{space 4}-.0869822{col 71}{space 3} .4651142
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1321611{col 30}{space 2} .0813677{col 41}{space 1}    1.62{col 50}{space 3}0.104{col 58}{space 4}-.0273166{col 71}{space 3} .2916389
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2510517{col 30}{space 2} .0561192{col 41}{space 1}    4.47{col 50}{space 3}0.000{col 58}{space 4}   .14106{col 71}{space 3} .3610433
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1340599{col 30}{space 2} .0438972{col 41}{space 1}   -3.05{col 50}{space 3}0.002{col 58}{space 4}-.2200968{col 71}{space 3} -.048023
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1126935{col 30}{space 2} .0359349{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4} .0422624{col 71}{space 3} .1831246
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0962443{col 30}{space 2}  .062407{col 41}{space 1}    1.54{col 50}{space 3}0.123{col 58}{space 4}-.0260712{col 71}{space 3} .2185598
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1439232{col 30}{space 2} .3352119{col 41}{space 1}    0.43{col 50}{space 3}0.668{col 58}{space 4}  -.51308{col 71}{space 3} .8009265
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6998549{col 30}{space 2} .1091614{col 41}{space 1}    6.41{col 50}{space 3}0.000{col 58}{space 4} .4859026{col 71}{space 3} .9138073
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8034316{col 30}{space 2} .1780722{col 41}{space 1}    4.51{col 50}{space 3}0.000{col 58}{space 4} .4544165{col 71}{space 3} 1.152447
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2635061{col 30}{space 2} .1165759{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0350215{col 71}{space 3} .4919908
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .235637{col 30}{space 2} .1000076{col 41}{space 1}    2.36{col 50}{space 3}0.018{col 58}{space 4} .0396258{col 71}{space 3} .4316483
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0457961{col 30}{space 2}   .03994{col 41}{space 1}   -1.15{col 50}{space 3}0.252{col 58}{space 4} -.124077{col 71}{space 3} .0324848
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .3235779{col 30}{space 2} .0612609{col 41}{space 1}    5.28{col 50}{space 3}0.000{col 58}{space 4} .2035087{col 71}{space 3} .4436471
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1149873{col 30}{space 2} .0501013{col 41}{space 1}    2.30{col 50}{space 3}0.022{col 58}{space 4} .0167906{col 71}{space 3} .2131839
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.391343{col 30}{space 2} .2146344{col 41}{space 1}   25.12{col 50}{space 3}0.000{col 58}{space 4} 4.970667{col 71}{space 3} 5.812019
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69630733
         {txt}sigma_e {c |} {res} 1.2890757
             {txt}rho {c |} {res} .22587017{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est22
{txt}
{com}. 
. 
. drop pdd9_6
{txt}
{com}. gen pdd9_6= pdd9_town
{txt}
{com}. xtreg hdd9  pdd9_6 sum_town  $xlist  pdd9_mean_town $year_MALAWI if country==6, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,626
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,571

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0215                                         {txt}min = {res}         1
{txt}     between = {res}0.3908                                         {txt}avg = {res}       2.9
{txt}     overall = {res}0.2755                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1555.06
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_6 {c |}{col 18}{res}{space 2} .0354293{col 30}{space 2} .0264804{col 41}{space 1}    1.34{col 50}{space 3}0.181{col 58}{space 4}-.0164712{col 71}{space 3} .0873299
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0133754{col 30}{space 2} .0035136{col 41}{space 1}   -3.81{col 50}{space 3}0.000{col 58}{space 4} -.020262{col 71}{space 3}-.0064889
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0008839{col 30}{space 2} .0111509{col 41}{space 1}   -0.08{col 50}{space 3}0.937{col 58}{space 4}-.0227393{col 71}{space 3} .0209715
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2563241{col 30}{space 2} .1031917{col 41}{space 1}   -2.48{col 50}{space 3}0.013{col 58}{space 4}-.4585762{col 71}{space 3} -.054072
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0013399{col 30}{space 2} .0017073{col 41}{space 1}   -0.78{col 50}{space 3}0.433{col 58}{space 4}-.0046861{col 71}{space 3} .0020062
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0905517{col 30}{space 2} .0600314{col 41}{space 1}   -1.51{col 50}{space 3}0.131{col 58}{space 4}-.2082112{col 71}{space 3} .0271077
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3133136{col 30}{space 2} .0585335{col 41}{space 1}    5.35{col 50}{space 3}0.000{col 58}{space 4}   .19859{col 71}{space 3} .4280372
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2609138{col 30}{space 2} .1918045{col 41}{space 1}    1.36{col 50}{space 3}0.174{col 58}{space 4}-.1150161{col 71}{space 3} .6368436
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1058968{col 30}{space 2} .0695855{col 41}{space 1}    1.52{col 50}{space 3}0.128{col 58}{space 4}-.0304882{col 71}{space 3} .2422818
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1962309{col 30}{space 2}  .140157{col 41}{space 1}    1.40{col 50}{space 3}0.161{col 58}{space 4}-.0784717{col 71}{space 3} .4709335
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1341625{col 30}{space 2} .0811883{col 41}{space 1}    1.65{col 50}{space 3}0.098{col 58}{space 4}-.0249636{col 71}{space 3} .2932886
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .252835{col 30}{space 2} .0561609{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .1427618{col 71}{space 3} .3629083
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1458804{col 30}{space 2} .0434658{col 41}{space 1}   -3.36{col 50}{space 3}0.001{col 58}{space 4}-.2310717{col 71}{space 3}-.0606891
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0988282{col 30}{space 2} .0347636{col 41}{space 1}    2.84{col 50}{space 3}0.004{col 58}{space 4} .0306929{col 71}{space 3} .1669635
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0927883{col 30}{space 2} .0621989{col 41}{space 1}    1.49{col 50}{space 3}0.136{col 58}{space 4}-.0291193{col 71}{space 3} .2146959
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0771413{col 30}{space 2} .3271422{col 41}{space 1}    0.24{col 50}{space 3}0.814{col 58}{space 4}-.5640457{col 71}{space 3} .7183283
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7097562{col 30}{space 2} .1090171{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4} .4960866{col 71}{space 3} .9234258
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8368963{col 30}{space 2} .1765777{col 41}{space 1}    4.74{col 50}{space 3}0.000{col 58}{space 4} .4908105{col 71}{space 3} 1.182982
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3303057{col 30}{space 2} .1145612{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .1057699{col 71}{space 3} .5548416
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2698569{col 30}{space 2} .1002771{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0733173{col 71}{space 3} .4663965
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}-.0372205{col 30}{space 2} .0393211{col 41}{space 1}   -0.95{col 50}{space 3}0.344{col 58}{space 4}-.1142883{col 71}{space 3} .0398474
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2618285{col 30}{space 2} .0559477{col 41}{space 1}    4.68{col 50}{space 3}0.000{col 58}{space 4}  .152173{col 71}{space 3} .3714839
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .111046{col 30}{space 2} .0497797{col 41}{space 1}    2.23{col 50}{space 3}0.026{col 58}{space 4} .0134796{col 71}{space 3} .2086124
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.262093{col 30}{space 2}  .222422{col 41}{space 1}   23.66{col 50}{space 3}0.000{col 58}{space 4} 4.826154{col 71}{space 3} 5.698032
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70045639
         {txt}sigma_e {c |} {res} 1.2904676
             {txt}rho {c |} {res}  .2275749{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est32
{txt}
{com}. 
. 
. drop pdd9_6
{txt}
{com}. gen pdd9_6= pdd9_dist
{txt}
{com}. xtreg hdd9  pdd9_6 sum_dist  $xlist  pdd9_mean_dist $year_MALAWI if country==6, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,626
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,571

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0217                                         {txt}min = {res}         1
{txt}     between = {res}0.3946                                         {txt}avg = {res}       2.9
{txt}     overall = {res}0.2768                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1533.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_6 {c |}{col 18}{res}{space 2}-.0427328{col 30}{space 2} .0416063{col 41}{space 1}   -1.03{col 50}{space 3}0.304{col 58}{space 4}-.1242796{col 71}{space 3} .0388139
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0039425{col 30}{space 2} .0009734{col 41}{space 1}   -4.05{col 50}{space 3}0.000{col 58}{space 4}-.0058503{col 71}{space 3}-.0020346
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0021482{col 30}{space 2}  .011228{col 41}{space 1}   -0.19{col 50}{space 3}0.848{col 58}{space 4}-.0241547{col 71}{space 3} .0198583
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.269356{col 30}{space 2} .1030895{col 41}{space 1}   -2.61{col 50}{space 3}0.009{col 58}{space 4}-.4714077{col 71}{space 3}-.0673043
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0017041{col 30}{space 2} .0017104{col 41}{space 1}   -1.00{col 50}{space 3}0.319{col 58}{space 4}-.0050563{col 71}{space 3} .0016482
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1063593{col 30}{space 2} .0598905{col 41}{space 1}   -1.78{col 50}{space 3}0.076{col 58}{space 4}-.2237426{col 71}{space 3}  .011024
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2998328{col 30}{space 2} .0585464{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4} .1850841{col 71}{space 3} .4145816
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2643125{col 30}{space 2} .1903361{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4}-.1087393{col 71}{space 3} .6373644
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1124799{col 30}{space 2} .0695981{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4}-.0239299{col 71}{space 3} .2488897
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2210991{col 30}{space 2} .1397919{col 41}{space 1}    1.58{col 50}{space 3}0.114{col 58}{space 4} -.052888{col 71}{space 3} .4950861
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1382601{col 30}{space 2} .0811021{col 41}{space 1}    1.70{col 50}{space 3}0.088{col 58}{space 4}-.0206971{col 71}{space 3} .2972173
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2579415{col 30}{space 2} .0561605{col 41}{space 1}    4.59{col 50}{space 3}0.000{col 58}{space 4}  .147869{col 71}{space 3} .3680141
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1630508{col 30}{space 2} .0432669{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.2478523{col 71}{space 3}-.0782492
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0918483{col 30}{space 2} .0337144{col 41}{space 1}    2.72{col 50}{space 3}0.006{col 58}{space 4} .0257693{col 71}{space 3} .1579274
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0908392{col 30}{space 2} .0620618{col 41}{space 1}    1.46{col 50}{space 3}0.143{col 58}{space 4}-.0307997{col 71}{space 3} .2124781
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0041397{col 30}{space 2} .3139129{col 41}{space 1}    0.01{col 50}{space 3}0.989{col 58}{space 4}-.6111183{col 71}{space 3} .6193976
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7179215{col 30}{space 2} .1081372{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .5059765{col 71}{space 3} .9298664
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8662439{col 30}{space 2} .1742381{col 41}{space 1}    4.97{col 50}{space 3}0.000{col 58}{space 4} .5247434{col 71}{space 3} 1.207744
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3508242{col 30}{space 2} .1140328{col 41}{space 1}    3.08{col 50}{space 3}0.002{col 58}{space 4}  .127324{col 71}{space 3} .5743244
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2763338{col 30}{space 2} .0997502{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4}  .080827{col 71}{space 3} .4718406
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0187495{col 30}{space 2} .0656245{col 41}{space 1}   -0.29{col 50}{space 3}0.775{col 58}{space 4}-.1473711{col 71}{space 3} .1098721
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2386601{col 30}{space 2} .0566011{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4} .1277241{col 71}{space 3} .3495962
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1035806{col 30}{space 2} .0498277{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0059202{col 71}{space 3}  .201241
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.714456{col 30}{space 2} .3751176{col 41}{space 1}   15.23{col 50}{space 3}0.000{col 58}{space 4} 4.979239{col 71}{space 3} 6.449673
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .6940838
         {txt}sigma_e {c |} {res} 1.2904179
             {txt}rho {c |} {res}  .2243912{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est42
{txt}
{com}. 
. 
. 
. 
. 
. *Niger
. gen pdd9_1=pdd9
{txt}
{com}. xtreg hdd9  pdd9_1   $xlist  pdd9_mean $year_NIGER if country==1, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,536
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,837

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0397                                         {txt}min = {res}         1
{txt}     between = {res}0.2213                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1727                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1348.56
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_1 {c |}{col 18}{res}{space 2} .2418613{col 30}{space 2} .0352713{col 41}{space 1}    6.86{col 50}{space 3}0.000{col 58}{space 4} .1727308{col 71}{space 3} .3109918
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .013393{col 30}{space 2} .0065958{col 41}{space 1}    2.03{col 50}{space 3}0.042{col 58}{space 4} .0004655{col 71}{space 3} .0263206
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1326112{col 30}{space 2} .1000549{col 41}{space 1}   -1.33{col 50}{space 3}0.185{col 58}{space 4}-.3287152{col 71}{space 3} .0634927
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0029101{col 30}{space 2} .0014282{col 41}{space 1}    2.04{col 50}{space 3}0.042{col 58}{space 4} .0001109{col 71}{space 3} .0057093
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .088006{col 30}{space 2} .0598281{col 41}{space 1}    1.47{col 50}{space 3}0.141{col 58}{space 4}-.0292549{col 71}{space 3} .2052669
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3483333{col 30}{space 2} .0456631{col 41}{space 1}    7.63{col 50}{space 3}0.000{col 58}{space 4} .2588353{col 71}{space 3} .4378313
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3006591{col 30}{space 2} .1106177{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0838524{col 71}{space 3} .5174658
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0893745{col 30}{space 2} .0780906{col 41}{space 1}    1.14{col 50}{space 3}0.252{col 58}{space 4}-.0636804{col 71}{space 3} .2424293
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3018629{col 30}{space 2} .1233802{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0600421{col 71}{space 3} .5436836
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1986832{col 30}{space 2} .0901497{col 41}{space 1}    2.20{col 50}{space 3}0.028{col 58}{space 4} .0219931{col 71}{space 3} .3753734
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1745724{col 30}{space 2} .0683925{col 41}{space 1}   -2.55{col 50}{space 3}0.011{col 58}{space 4}-.3086192{col 71}{space 3}-.0405256
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1318193{col 30}{space 2} .0453711{col 41}{space 1}   -2.91{col 50}{space 3}0.004{col 58}{space 4}-.2207452{col 71}{space 3}-.0428935
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0014132{col 30}{space 2} .0015757{col 41}{space 1}   -0.90{col 50}{space 3}0.370{col 58}{space 4}-.0045015{col 71}{space 3} .0016752
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2083843{col 30}{space 2} .2164151{col 41}{space 1}    0.96{col 50}{space 3}0.336{col 58}{space 4}-.2157814{col 71}{space 3} .6325501
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0526337{col 30}{space 2} .1330637{col 41}{space 1}    0.40{col 50}{space 3}0.692{col 58}{space 4}-.2081664{col 71}{space 3} .3134337
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3337707{col 30}{space 2} .0954013{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4} .1467876{col 71}{space 3} .5207538
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .407959{col 30}{space 2} .1404658{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4}  .132651{col 71}{space 3}  .683267
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2162789{col 30}{space 2} .1109317{col 41}{space 1}    1.95{col 50}{space 3}0.051{col 58}{space 4}-.0011432{col 71}{space 3}  .433701
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4538957{col 30}{space 2} .0840805{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .2891009{col 71}{space 3} .6186906
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2567401{col 30}{space 2} .0401505{col 41}{space 1}   -6.39{col 50}{space 3}0.000{col 58}{space 4}-.3354336{col 71}{space 3}-.1780466
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2550797{col 30}{space 2}  .038422{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4}  .179774{col 71}{space 3} .3303855
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.580461{col 30}{space 2} .1107819{col 41}{space 1}   41.35{col 50}{space 3}0.000{col 58}{space 4} 4.363332{col 71}{space 3} 4.797589
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .56375272
         {txt}sigma_e {c |} {res} 1.3958609
             {txt}rho {c |} {res} .14023955{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est13
{txt}
{com}. 
. drop pdd9_1
{txt}
{com}. gen pdd9_1= pdd9_vill
{txt}
{com}. xtreg hdd9  pdd9_1 sum_vill  $xlist  pdd9_mean_vill $year_NIGER if country==1, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,536
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,837

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0237                                         {txt}min = {res}         1
{txt}     between = {res}0.2450                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1839                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1450.23
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_1 {c |}{col 18}{res}{space 2} .1124152{col 30}{space 2} .0308949{col 41}{space 1}    3.64{col 50}{space 3}0.000{col 58}{space 4} .0518623{col 71}{space 3} .1729681
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0626683{col 30}{space 2} .0063129{col 41}{space 1}   -9.93{col 50}{space 3}0.000{col 58}{space 4}-.0750413{col 71}{space 3}-.0502954
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0192368{col 30}{space 2} .0063327{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4}  .006825{col 71}{space 3} .0316486
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0956448{col 30}{space 2} .0997031{col 41}{space 1}   -0.96{col 50}{space 3}0.337{col 58}{space 4}-.2910592{col 71}{space 3} .0997696
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0013645{col 30}{space 2} .0014196{col 41}{space 1}    0.96{col 50}{space 3}0.336{col 58}{space 4}-.0014179{col 71}{space 3}  .004147
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0453697{col 30}{space 2} .0587459{col 41}{space 1}    0.77{col 50}{space 3}0.440{col 58}{space 4}-.0697702{col 71}{space 3} .1605095
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3347186{col 30}{space 2} .0453829{col 41}{space 1}    7.38{col 50}{space 3}0.000{col 58}{space 4} .2457697{col 71}{space 3} .4236675
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .325666{col 30}{space 2} .1119055{col 41}{space 1}    2.91{col 50}{space 3}0.004{col 58}{space 4} .1063351{col 71}{space 3} .5449968
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1031145{col 30}{space 2} .0790499{col 41}{space 1}    1.30{col 50}{space 3}0.192{col 58}{space 4}-.0518204{col 71}{space 3} .2580495
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2284768{col 30}{space 2} .1255288{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4}-.0175552{col 71}{space 3} .4745088
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2107766{col 30}{space 2} .0909195{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0325777{col 71}{space 3} .3889755
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1613506{col 30}{space 2} .0696526{col 41}{space 1}   -2.32{col 50}{space 3}0.021{col 58}{space 4}-.2978672{col 71}{space 3} -.024834
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0678166{col 30}{space 2} .0453556{col 41}{space 1}   -1.50{col 50}{space 3}0.135{col 58}{space 4} -.156712{col 71}{space 3} .0210788
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0007767{col 30}{space 2}  .001508{col 41}{space 1}   -0.52{col 50}{space 3}0.606{col 58}{space 4}-.0037323{col 71}{space 3} .0021788
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3001149{col 30}{space 2} .2190299{col 41}{space 1}    1.37{col 50}{space 3}0.171{col 58}{space 4}-.1291757{col 71}{space 3} .7294056
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0007937{col 30}{space 2}  .133915{col 41}{space 1}   -0.01{col 50}{space 3}0.995{col 58}{space 4}-.2632623{col 71}{space 3} .2616749
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1409804{col 30}{space 2} .0971091{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4}-.0493499{col 71}{space 3} .3313107
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2012897{col 30}{space 2} .1448711{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4}-.0826524{col 71}{space 3} .4852319
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0581451{col 30}{space 2} .1112941{col 41}{space 1}    0.52{col 50}{space 3}0.601{col 58}{space 4}-.1599874{col 71}{space 3} .2762776
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3640445{col 30}{space 2} .0853135{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .1968332{col 71}{space 3} .5312558
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0477788{col 30}{space 2} .0354841{col 41}{space 1}   -1.35{col 50}{space 3}0.178{col 58}{space 4}-.1173262{col 71}{space 3} .0217687
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2807444{col 30}{space 2} .0392336{col 41}{space 1}    7.16{col 50}{space 3}0.000{col 58}{space 4} .2038479{col 71}{space 3} .3576408
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.304629{col 30}{space 2} .1361428{col 41}{space 1}   38.96{col 50}{space 3}0.000{col 58}{space 4} 5.037793{col 71}{space 3} 5.571464
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .50240752
         {txt}sigma_e {c |} {res} 1.4060479
             {txt}rho {c |} {res}  .1132211{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est23
{txt}
{com}. 
. 
. drop pdd9_1
{txt}
{com}. gen pdd9_1= pdd9_town
{txt}
{com}. xtreg hdd9  pdd9_1 sum_town  $xlist  pdd9_mean_town $year_NIGER if country==1, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,536
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,837

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0258                                         {txt}min = {res}         1
{txt}     between = {res}0.2263                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1735                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1391.18
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_1 {c |}{col 18}{res}{space 2} .0795844{col 30}{space 2} .0299892{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4} .0208066{col 71}{space 3} .1383622
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0014016{col 30}{space 2} .0003267{col 41}{space 1}   -4.29{col 50}{space 3}0.000{col 58}{space 4}-.0020419{col 71}{space 3}-.0007612
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0112542{col 30}{space 2} .0064052{col 41}{space 1}    1.76{col 50}{space 3}0.079{col 58}{space 4}-.0012998{col 71}{space 3} .0238081
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.144688{col 30}{space 2} .0992959{col 41}{space 1}   -1.46{col 50}{space 3}0.145{col 58}{space 4}-.3393043{col 71}{space 3} .0499284
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0032267{col 30}{space 2}   .00142{col 41}{space 1}    2.27{col 50}{space 3}0.023{col 58}{space 4} .0004435{col 71}{space 3}   .00601
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0962279{col 30}{space 2} .0588911{col 41}{space 1}    1.63{col 50}{space 3}0.102{col 58}{space 4}-.0191965{col 71}{space 3} .2116524
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3536739{col 30}{space 2} .0461326{col 41}{space 1}    7.67{col 50}{space 3}0.000{col 58}{space 4} .2632558{col 71}{space 3} .4440921
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .338598{col 30}{space 2} .1116514{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .1197653{col 71}{space 3} .5574306
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1150273{col 30}{space 2} .0786894{col 41}{space 1}    1.46{col 50}{space 3}0.144{col 58}{space 4} -.039201{col 71}{space 3} .2692556
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2636178{col 30}{space 2} .1251279{col 41}{space 1}    2.11{col 50}{space 3}0.035{col 58}{space 4} .0183717{col 71}{space 3} .5088639
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2104011{col 30}{space 2} .0909576{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4} .0321275{col 71}{space 3} .3886747
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1609286{col 30}{space 2} .0698679{col 41}{space 1}   -2.30{col 50}{space 3}0.021{col 58}{space 4}-.2978672{col 71}{space 3}-.0239901
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1416447{col 30}{space 2} .0450748{col 41}{space 1}   -3.14{col 50}{space 3}0.002{col 58}{space 4}-.2299897{col 71}{space 3}-.0532996
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0017266{col 30}{space 2} .0015604{col 41}{space 1}   -1.11{col 50}{space 3}0.269{col 58}{space 4}-.0047848{col 71}{space 3} .0013317
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2147425{col 30}{space 2} .2161232{col 41}{space 1}    0.99{col 50}{space 3}0.320{col 58}{space 4}-.2088512{col 71}{space 3} .6383361
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0093779{col 30}{space 2} .1340446{col 41}{space 1}    0.07{col 50}{space 3}0.944{col 58}{space 4}-.2533446{col 71}{space 3} .2721005
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2901944{col 30}{space 2} .0962768{col 41}{space 1}    3.01{col 50}{space 3}0.003{col 58}{space 4} .1014952{col 71}{space 3} .4788935
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5113504{col 30}{space 2} .1412556{col 41}{space 1}    3.62{col 50}{space 3}0.000{col 58}{space 4} .2344946{col 71}{space 3} .7882063
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .179261{col 30}{space 2} .1114683{col 41}{space 1}    1.61{col 50}{space 3}0.108{col 58}{space 4}-.0392128{col 71}{space 3} .3977348
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4040704{col 30}{space 2} .0852851{col 41}{space 1}    4.74{col 50}{space 3}0.000{col 58}{space 4} .2369146{col 71}{space 3} .5712262
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}  .048287{col 30}{space 2} .0365711{col 41}{space 1}    1.32{col 50}{space 3}0.187{col 58}{space 4} -.023391{col 71}{space 3}  .119965
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2499507{col 30}{space 2} .0391397{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .1732383{col 71}{space 3}  .326663
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.948392{col 30}{space 2} .1467919{col 41}{space 1}   26.90{col 50}{space 3}0.000{col 58}{space 4} 3.660685{col 71}{space 3} 4.236099
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .55335731
         {txt}sigma_e {c |} {res} 1.3965162
             {txt}rho {c |} {res} .13570109{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est33
{txt}
{com}. 
. 
. drop pdd9_1
{txt}
{com}. gen pdd9_1= pdd9_dist
{txt}
{com}. xtreg hdd9  pdd9_1 sum_dist  $xlist  pdd9_mean_dist $year_NIGER if country==1, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,536
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,837

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0217                                         {txt}min = {res}         1
{txt}     between = {res}0.2269                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1715                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1329.24
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_1 {c |}{col 18}{res}{space 2} .0280138{col 30}{space 2} .0443403{col 41}{space 1}    0.63{col 50}{space 3}0.528{col 58}{space 4}-.0588916{col 71}{space 3} .1149192
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0004621{col 30}{space 2} .0002761{col 41}{space 1}    1.67{col 50}{space 3}0.094{col 58}{space 4}-.0000791{col 71}{space 3} .0010033
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0138417{col 30}{space 2} .0063937{col 41}{space 1}    2.16{col 50}{space 3}0.030{col 58}{space 4} .0013102{col 71}{space 3} .0263733
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1308327{col 30}{space 2} .0997915{col 41}{space 1}   -1.31{col 50}{space 3}0.190{col 58}{space 4}-.3264205{col 71}{space 3}  .064755
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0029147{col 30}{space 2} .0014241{col 41}{space 1}    2.05{col 50}{space 3}0.041{col 58}{space 4} .0001235{col 71}{space 3} .0057059
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0796704{col 30}{space 2} .0590139{col 41}{space 1}    1.35{col 50}{space 3}0.177{col 58}{space 4}-.0359948{col 71}{space 3} .1953355
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3602885{col 30}{space 2} .0461414{col 41}{space 1}    7.81{col 50}{space 3}0.000{col 58}{space 4}  .269853{col 71}{space 3}  .450724
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3392855{col 30}{space 2} .1115464{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .1206585{col 71}{space 3} .5579125
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1178639{col 30}{space 2} .0789948{col 41}{space 1}    1.49{col 50}{space 3}0.136{col 58}{space 4}-.0369631{col 71}{space 3} .2726908
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2600981{col 30}{space 2} .1250755{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0149546{col 71}{space 3} .5052415
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2209914{col 30}{space 2} .0910413{col 41}{space 1}    2.43{col 50}{space 3}0.015{col 58}{space 4} .0425537{col 71}{space 3}  .399429
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1571584{col 30}{space 2}  .070024{col 41}{space 1}   -2.24{col 50}{space 3}0.025{col 58}{space 4}-.2944028{col 71}{space 3} -.019914
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1152895{col 30}{space 2} .0453972{col 41}{space 1}   -2.54{col 50}{space 3}0.011{col 58}{space 4}-.2042664{col 71}{space 3}-.0263126
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0008811{col 30}{space 2} .0015428{col 41}{space 1}   -0.57{col 50}{space 3}0.568{col 58}{space 4}-.0039049{col 71}{space 3} .0021426
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2143656{col 30}{space 2} .2173695{col 41}{space 1}    0.99{col 50}{space 3}0.324{col 58}{space 4}-.2116709{col 71}{space 3}  .640402
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0077269{col 30}{space 2} .1340696{col 41}{space 1}   -0.06{col 50}{space 3}0.954{col 58}{space 4}-.2704986{col 71}{space 3} .2550448
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3010089{col 30}{space 2} .0959762{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4}  .112899{col 71}{space 3} .4891188
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4569079{col 30}{space 2} .1410132{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .1805271{col 71}{space 3} .7332888
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1801128{col 30}{space 2} .1114804{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4}-.0383848{col 71}{space 3} .3986105
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4085646{col 30}{space 2} .0855039{col 41}{space 1}    4.78{col 50}{space 3}0.000{col 58}{space 4} .2409801{col 71}{space 3} .5761491
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0603026{col 30}{space 2} .0530092{col 41}{space 1}    1.14{col 50}{space 3}0.255{col 58}{space 4}-.0435936{col 71}{space 3} .1641987
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2382424{col 30}{space 2} .0389254{col 41}{space 1}    6.12{col 50}{space 3}0.000{col 58}{space 4} .1619499{col 71}{space 3} .3145348
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.915618{col 30}{space 2} .1944536{col 41}{space 1}   20.14{col 50}{space 3}0.000{col 58}{space 4} 3.534496{col 71}{space 3}  4.29674
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .54604504
         {txt}sigma_e {c |} {res} 1.4004196
             {txt}rho {c |} {res} .13197002{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est43
{txt}
{com}. 
. 
. 
. *Nigeria
. gen pdd9_2=pdd9
{txt}
{com}. xtreg hdd9  pdd9_2   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    15,063
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,154

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0356                                         {txt}min = {res}         1
{txt}     between = {res}0.2969                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.2534                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3871.97
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_2 {c |}{col 18}{res}{space 2} .0797371{col 30}{space 2} .0155474{col 41}{space 1}    5.13{col 50}{space 3}0.000{col 58}{space 4} .0492648{col 71}{space 3} .1102094
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0293148{col 30}{space 2} .0046704{col 41}{space 1}   -6.28{col 50}{space 3}0.000{col 58}{space 4}-.0384687{col 71}{space 3} -.020161
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1558158{col 30}{space 2} .0540154{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0499477{col 71}{space 3}  .261684
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0046601{col 30}{space 2} .0009741{col 41}{space 1}    4.78{col 50}{space 3}0.000{col 58}{space 4} .0027509{col 71}{space 3} .0065693
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3154281{col 30}{space 2} .0392348{col 41}{space 1}    8.04{col 50}{space 3}0.000{col 58}{space 4} .2385293{col 71}{space 3} .3923269
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1907751{col 30}{space 2} .0286926{col 41}{space 1}    6.65{col 50}{space 3}0.000{col 58}{space 4} .1345385{col 71}{space 3} .2470116
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0158238{col 30}{space 2} .0419055{col 41}{space 1}    0.38{col 50}{space 3}0.706{col 58}{space 4}-.0663094{col 71}{space 3} .0979571
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1632202{col 30}{space 2} .0406531{col 41}{space 1}    4.01{col 50}{space 3}0.000{col 58}{space 4} .0835416{col 71}{space 3} .2428988
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0827451{col 30}{space 2} .0495446{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0143606{col 71}{space 3} .1798508
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2569157{col 30}{space 2} .0571459{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .1449117{col 71}{space 3} .3689197
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3082281{col 30}{space 2} .0434577{col 41}{space 1}    7.09{col 50}{space 3}0.000{col 58}{space 4} .2230526{col 71}{space 3} .3934036
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0334789{col 30}{space 2} .0470724{col 41}{space 1}    0.71{col 50}{space 3}0.477{col 58}{space 4}-.0587814{col 71}{space 3} .1257392
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0087572{col 30}{space 2} .0068021{col 41}{space 1}   -1.29{col 50}{space 3}0.198{col 58}{space 4}-.0220891{col 71}{space 3} .0045746
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3341661{col 30}{space 2} .0605789{col 41}{space 1}    5.52{col 50}{space 3}0.000{col 58}{space 4} .2154337{col 71}{space 3} .4528985
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0645349{col 30}{space 2} .0571875{col 41}{space 1}    1.13{col 50}{space 3}0.259{col 58}{space 4}-.0475506{col 71}{space 3} .1766204
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7715254{col 30}{space 2}  .060225{col 41}{space 1}   12.81{col 50}{space 3}0.000{col 58}{space 4} .6534864{col 71}{space 3} .8895643
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8428912{col 30}{space 2} .0617761{col 41}{space 1}   13.64{col 50}{space 3}0.000{col 58}{space 4} .7218123{col 71}{space 3} .9639701
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1399659{col 30}{space 2} .0743895{col 41}{space 1}    1.88{col 50}{space 3}0.060{col 58}{space 4}-.0058349{col 71}{space 3} .2857666
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0525943{col 30}{space 2} .0556421{col 41}{space 1}   -0.95{col 50}{space 3}0.345{col 58}{space 4}-.1616508{col 71}{space 3} .0564623
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0337268{col 30}{space 2} .0201497{col 41}{space 1}   -1.67{col 50}{space 3}0.094{col 58}{space 4}-.0732195{col 71}{space 3} .0057659
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5672983{col 30}{space 2} .0333552{col 41}{space 1}  -17.01{col 50}{space 3}0.000{col 58}{space 4}-.6326732{col 71}{space 3}-.5019233
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5147852{col 30}{space 2} .0337128{col 41}{space 1}  -15.27{col 50}{space 3}0.000{col 58}{space 4}-.5808611{col 71}{space 3}-.4487092
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} -.372811{col 30}{space 2} .0335485{col 41}{space 1}  -11.11{col 50}{space 3}0.000{col 58}{space 4}-.4385649{col 71}{space 3} -.307057
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.474605{col 30}{space 2} .0796199{col 41}{space 1}   56.20{col 50}{space 3}0.000{col 58}{space 4} 4.318553{col 71}{space 3} 4.630658
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .86808159
         {txt}sigma_e {c |} {res} 1.2228102
             {txt}rho {c |} {res} .33509226{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est14
{txt}
{com}. 
. drop pdd9_2
{txt}
{com}. gen pdd9_2= pdd9_vill
{txt}
{com}. xtreg hdd9  pdd9_2 sum_vill  $xlist  pdd9_mean_vill $year_NIGERIA if country==2, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    15,063
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,154

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0348                                         {txt}min = {res}         1
{txt}     between = {res}0.3218                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.2718                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  4396.16
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_2 {c |}{col 18}{res}{space 2} .0665621{col 30}{space 2} .0156285{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .0359308{col 71}{space 3} .0971935
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0918446{col 30}{space 2} .0071897{col 41}{space 1}  -12.77{col 50}{space 3}0.000{col 58}{space 4}-.1059361{col 71}{space 3}-.0777531
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0145126{col 30}{space 2} .0046655{col 41}{space 1}   -3.11{col 50}{space 3}0.002{col 58}{space 4}-.0236567{col 71}{space 3}-.0053684
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .148199{col 30}{space 2} .0536325{col 41}{space 1}    2.76{col 50}{space 3}0.006{col 58}{space 4} .0430811{col 71}{space 3} .2533168
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0031477{col 30}{space 2} .0009595{col 41}{space 1}    3.28{col 50}{space 3}0.001{col 58}{space 4} .0012671{col 71}{space 3} .0050282
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2558029{col 30}{space 2} .0389368{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .1794881{col 71}{space 3} .3321176
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .174215{col 30}{space 2} .0283255{col 41}{space 1}    6.15{col 50}{space 3}0.000{col 58}{space 4}  .118698{col 71}{space 3} .2297321
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0197481{col 30}{space 2}  .041746{col 41}{space 1}    0.47{col 50}{space 3}0.636{col 58}{space 4}-.0620725{col 71}{space 3} .1015687
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1644638{col 30}{space 2} .0406247{col 41}{space 1}    4.05{col 50}{space 3}0.000{col 58}{space 4} .0848407{col 71}{space 3} .2440868
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0750757{col 30}{space 2} .0496386{col 41}{space 1}    1.51{col 50}{space 3}0.130{col 58}{space 4}-.0222141{col 71}{space 3} .1723655
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2396506{col 30}{space 2} .0571545{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .1276298{col 71}{space 3} .3516715
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2994436{col 30}{space 2} .0434613{col 41}{space 1}    6.89{col 50}{space 3}0.000{col 58}{space 4}  .214261{col 71}{space 3} .3846261
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  .068658{col 30}{space 2} .0465523{col 41}{space 1}    1.47{col 50}{space 3}0.140{col 58}{space 4} -.022583{col 71}{space 3} .1598989
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.003663{col 30}{space 2} .0051975{col 41}{space 1}   -0.70{col 50}{space 3}0.481{col 58}{space 4}-.0138499{col 71}{space 3}  .006524
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3330388{col 30}{space 2} .0602463{col 41}{space 1}    5.53{col 50}{space 3}0.000{col 58}{space 4} .2149583{col 71}{space 3} .4511194
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0776086{col 30}{space 2}  .056332{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0328002{col 71}{space 3} .1880173
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6845126{col 30}{space 2} .0598609{col 41}{space 1}   11.44{col 50}{space 3}0.000{col 58}{space 4} .5671873{col 71}{space 3} .8018378
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7066672{col 30}{space 2} .0616084{col 41}{space 1}   11.47{col 50}{space 3}0.000{col 58}{space 4} .5859169{col 71}{space 3} .8274174
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1029355{col 30}{space 2} .0740987{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4}-.0422952{col 71}{space 3} .2481662
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0766808{col 30}{space 2} .0550911{col 41}{space 1}   -1.39{col 50}{space 3}0.164{col 58}{space 4}-.1846574{col 71}{space 3} .0312959
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1355826{col 30}{space 2} .0195451{col 41}{space 1}    6.94{col 50}{space 3}0.000{col 58}{space 4}  .097275{col 71}{space 3} .1738903
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5462053{col 30}{space 2} .0332336{col 41}{space 1}  -16.44{col 50}{space 3}0.000{col 58}{space 4} -.611342{col 71}{space 3}-.4810687
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5154357{col 30}{space 2} .0336155{col 41}{space 1}  -15.33{col 50}{space 3}0.000{col 58}{space 4}-.5813208{col 71}{space 3}-.4495506
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3872107{col 30}{space 2} .0336675{col 41}{space 1}  -11.50{col 50}{space 3}0.000{col 58}{space 4}-.4531978{col 71}{space 3}-.3212237
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.568941{col 30}{space 2} .1022116{col 41}{space 1}   44.70{col 50}{space 3}0.000{col 58}{space 4}  4.36861{col 71}{space 3} 4.769272
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .83144873
         {txt}sigma_e {c |} {res} 1.2234985
             {txt}rho {c |} {res} .31591694{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est24
{txt}
{com}. 
. 
. drop pdd9_2
{txt}
{com}. gen pdd9_2= pdd9_town
{txt}
{com}. xtreg hdd9  pdd9_2 sum_town  $xlist  pdd9_mean_town $year_NIGERIA if country==2, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    15,063
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,154

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0355                                         {txt}min = {res}         1
{txt}     between = {res}0.3122                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.2659                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  4233.22
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_2 {c |}{col 18}{res}{space 2} .0667879{col 30}{space 2} .0151278{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .0371379{col 71}{space 3} .0964379
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0192483{col 30}{space 2} .0025452{col 41}{space 1}   -7.56{col 50}{space 3}0.000{col 58}{space 4}-.0242367{col 71}{space 3}-.0142599
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0200674{col 30}{space 2} .0046374{col 41}{space 1}   -4.33{col 50}{space 3}0.000{col 58}{space 4}-.0291564{col 71}{space 3}-.0109784
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .155521{col 30}{space 2}  .053633{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0504022{col 71}{space 3} .2606398
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .003644{col 30}{space 2} .0009645{col 41}{space 1}    3.78{col 50}{space 3}0.000{col 58}{space 4} .0017537{col 71}{space 3} .0055343
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2851424{col 30}{space 2} .0390102{col 41}{space 1}    7.31{col 50}{space 3}0.000{col 58}{space 4} .2086838{col 71}{space 3}  .361601
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1812109{col 30}{space 2} .0284207{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .1255073{col 71}{space 3} .2369146
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0157132{col 30}{space 2} .0417953{col 41}{space 1}    0.38{col 50}{space 3}0.707{col 58}{space 4}-.0662041{col 71}{space 3} .0976305
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1671488{col 30}{space 2}  .040623{col 41}{space 1}    4.11{col 50}{space 3}0.000{col 58}{space 4} .0875293{col 71}{space 3} .2467684
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0749593{col 30}{space 2} .0494861{col 41}{space 1}    1.51{col 50}{space 3}0.130{col 58}{space 4}-.0220317{col 71}{space 3} .1719502
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2458455{col 30}{space 2} .0570914{col 41}{space 1}    4.31{col 50}{space 3}0.000{col 58}{space 4} .1339485{col 71}{space 3} .3577425
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3063778{col 30}{space 2} .0434631{col 41}{space 1}    7.05{col 50}{space 3}0.000{col 58}{space 4} .2211917{col 71}{space 3}  .391564
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0485843{col 30}{space 2} .0467535{col 41}{space 1}    1.04{col 50}{space 3}0.299{col 58}{space 4}-.0430509{col 71}{space 3} .1402195
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.005316{col 30}{space 2} .0059406{col 41}{space 1}   -0.89{col 50}{space 3}0.371{col 58}{space 4}-.0169594{col 71}{space 3} .0063274
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3363599{col 30}{space 2} .0604133{col 41}{space 1}    5.57{col 50}{space 3}0.000{col 58}{space 4}  .217952{col 71}{space 3} .4547678
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0482978{col 30}{space 2} .0565675{col 41}{space 1}    0.85{col 50}{space 3}0.393{col 58}{space 4}-.0625723{col 71}{space 3}  .159168
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7352137{col 30}{space 2} .0597581{col 41}{space 1}   12.30{col 50}{space 3}0.000{col 58}{space 4} .6180899{col 71}{space 3} .8523375
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8144564{col 30}{space 2} .0610692{col 41}{space 1}   13.34{col 50}{space 3}0.000{col 58}{space 4} .6947629{col 71}{space 3} .9341498
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1579555{col 30}{space 2} .0739629{col 41}{space 1}    2.14{col 50}{space 3}0.033{col 58}{space 4} .0129909{col 71}{space 3} .3029201
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0465711{col 30}{space 2} .0552215{col 41}{space 1}   -0.84{col 50}{space 3}0.399{col 58}{space 4}-.1548032{col 71}{space 3}  .061661
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1157861{col 30}{space 2} .0193973{col 41}{space 1}    5.97{col 50}{space 3}0.000{col 58}{space 4} .0777681{col 71}{space 3} .1538041
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5581672{col 30}{space 2} .0342242{col 41}{space 1}  -16.31{col 50}{space 3}0.000{col 58}{space 4}-.6252454{col 71}{space 3} -.491089
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5082787{col 30}{space 2} .0346153{col 41}{space 1}  -14.68{col 50}{space 3}0.000{col 58}{space 4}-.5761234{col 71}{space 3}-.4404341
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3663143{col 30}{space 2} .0346864{col 41}{space 1}  -10.56{col 50}{space 3}0.000{col 58}{space 4}-.4342984{col 71}{space 3}-.2983302
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.977114{col 30}{space 2} .0933887{col 41}{space 1}   42.59{col 50}{space 3}0.000{col 58}{space 4} 3.794075{col 71}{space 3} 4.160152
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .84623051
         {txt}sigma_e {c |} {res} 1.2232495
             {txt}rho {c |} {res} .32367174{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est34
{txt}
{com}. 
. 
. drop pdd9_2
{txt}
{com}. gen pdd9_2= pdd9_dist
{txt}
{com}. xtreg hdd9  pdd9_2 sum_dist  $xlist  pdd9_mean_dist $year_NIGERIA if country==2, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    15,063
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,154

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0387                                         {txt}min = {res}         1
{txt}     between = {res}0.3033                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.2575                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  4029.91
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_2 {c |}{col 18}{res}{space 2} .1108346{col 30}{space 2} .0200641{col 41}{space 1}    5.52{col 50}{space 3}0.000{col 58}{space 4} .0715096{col 71}{space 3} .1501596
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0035127{col 30}{space 2} .0003529{col 41}{space 1}   -9.95{col 50}{space 3}0.000{col 58}{space 4}-.0042044{col 71}{space 3} -.002821
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0215824{col 30}{space 2} .0046646{col 41}{space 1}   -4.63{col 50}{space 3}0.000{col 58}{space 4} -.030725{col 71}{space 3}-.0124399
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1369363{col 30}{space 2} .0539404{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .0312151{col 71}{space 3} .2426576
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0049665{col 30}{space 2} .0009687{col 41}{space 1}    5.13{col 50}{space 3}0.000{col 58}{space 4} .0030678{col 71}{space 3} .0068651
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3057108{col 30}{space 2} .0392666{col 41}{space 1}    7.79{col 50}{space 3}0.000{col 58}{space 4} .2287497{col 71}{space 3} .3826719
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2000568{col 30}{space 2} .0286167{col 41}{space 1}    6.99{col 50}{space 3}0.000{col 58}{space 4}  .143969{col 71}{space 3} .2561445
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0152803{col 30}{space 2} .0418486{col 41}{space 1}    0.37{col 50}{space 3}0.715{col 58}{space 4}-.0667415{col 71}{space 3}  .097302
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1623581{col 30}{space 2} .0405444{col 41}{space 1}    4.00{col 50}{space 3}0.000{col 58}{space 4} .0828926{col 71}{space 3} .2418236
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0839806{col 30}{space 2}   .04927{col 41}{space 1}    1.70{col 50}{space 3}0.088{col 58}{space 4}-.0125867{col 71}{space 3}  .180548
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .244721{col 30}{space 2} .0572544{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .1325044{col 71}{space 3} .3569376
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3022339{col 30}{space 2}  .043348{col 41}{space 1}    6.97{col 50}{space 3}0.000{col 58}{space 4} .2172733{col 71}{space 3} .3871944
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0303851{col 30}{space 2} .0468014{col 41}{space 1}    0.65{col 50}{space 3}0.516{col 58}{space 4}-.0613439{col 71}{space 3} .1221142
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.005451{col 30}{space 2} .0059804{col 41}{space 1}   -0.91{col 50}{space 3}0.362{col 58}{space 4}-.0171723{col 71}{space 3} .0062703
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2940182{col 30}{space 2} .0603557{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .1757232{col 71}{space 3} .4123133
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0945555{col 30}{space 2} .0565099{col 41}{space 1}    1.67{col 50}{space 3}0.094{col 58}{space 4}-.0162019{col 71}{space 3} .2053128
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7441403{col 30}{space 2} .0601907{col 41}{space 1}   12.36{col 50}{space 3}0.000{col 58}{space 4} .6261686{col 71}{space 3}  .862112
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8025566{col 30}{space 2} .0612616{col 41}{space 1}   13.10{col 50}{space 3}0.000{col 58}{space 4} .6824861{col 71}{space 3} .9226272
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1061265{col 30}{space 2} .0742279{col 41}{space 1}    1.43{col 50}{space 3}0.153{col 58}{space 4}-.0393574{col 71}{space 3} .2516105
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0878694{col 30}{space 2}  .055458{col 41}{space 1}   -1.58{col 50}{space 3}0.113{col 58}{space 4}-.1965651{col 71}{space 3} .0208264
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0493682{col 30}{space 2} .0272854{col 41}{space 1}   -1.81{col 50}{space 3}0.070{col 58}{space 4}-.1028467{col 71}{space 3} .0041102
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5865297{col 30}{space 2} .0357736{col 41}{space 1}  -16.40{col 50}{space 3}0.000{col 58}{space 4}-.6566446{col 71}{space 3}-.5164147
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5243649{col 30}{space 2} .0364531{col 41}{space 1}  -14.38{col 50}{space 3}0.000{col 58}{space 4}-.5958116{col 71}{space 3}-.4529181
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3804863{col 30}{space 2} .0368997{col 41}{space 1}  -10.31{col 50}{space 3}0.000{col 58}{space 4}-.4528084{col 71}{space 3}-.3081643
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.518663{col 30}{space 2} .1694326{col 41}{space 1}   26.67{col 50}{space 3}0.000{col 58}{space 4} 4.186581{col 71}{space 3} 4.850745
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .86132363
         {txt}sigma_e {c |} {res} 1.2207038
             {txt}rho {c |} {res} .33238337{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est44
{txt}
{com}. 
. 
. *Tanzania
. gen pdd9_5=pdd9
{txt}
{com}. xtreg hdd9  pdd9_5   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,830
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,710

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0434                                         {txt}min = {res}         1
{txt}     between = {res}0.2265                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1812                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  2101.06
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_5 {c |}{col 18}{res}{space 2} .1931047{col 30}{space 2} .0136841{col 41}{space 1}   14.11{col 50}{space 3}0.000{col 58}{space 4} .1662844{col 71}{space 3}  .219925
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0093469{col 30}{space 2} .0054007{col 41}{space 1}   -1.73{col 50}{space 3}0.084{col 58}{space 4}-.0199322{col 71}{space 3} .0012383
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0479867{col 30}{space 2} .0651529{col 41}{space 1}    0.74{col 50}{space 3}0.461{col 58}{space 4}-.0797106{col 71}{space 3} .1756841
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0022084{col 30}{space 2} .0010512{col 41}{space 1}   -2.10{col 50}{space 3}0.036{col 58}{space 4}-.0042687{col 71}{space 3}-.0001482
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0494775{col 30}{space 2} .0370294{col 41}{space 1}    1.34{col 50}{space 3}0.181{col 58}{space 4}-.0230988{col 71}{space 3} .1220538
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2753447{col 30}{space 2} .0351178{col 41}{space 1}    7.84{col 50}{space 3}0.000{col 58}{space 4} .2065151{col 71}{space 3} .3441742
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2532299{col 30}{space 2} .0848296{col 41}{space 1}    2.99{col 50}{space 3}0.003{col 58}{space 4} .0869668{col 71}{space 3}  .419493
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2435248{col 30}{space 2} .0478541{col 41}{space 1}    5.09{col 50}{space 3}0.000{col 58}{space 4} .1497325{col 71}{space 3} .3373172
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0512096{col 30}{space 2} .0549581{col 41}{space 1}    0.93{col 50}{space 3}0.351{col 58}{space 4}-.0565064{col 71}{space 3} .1589255
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1071934{col 30}{space 2} .0383951{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0319404{col 71}{space 3} .1824463
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2110457{col 30}{space 2}  .040364{col 41}{space 1}    5.23{col 50}{space 3}0.000{col 58}{space 4} .1319337{col 71}{space 3} .2901576
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1731841{col 30}{space 2} .0337737{col 41}{space 1}   -5.13{col 50}{space 3}0.000{col 58}{space 4}-.2393793{col 71}{space 3}-.1069888
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0019761{col 30}{space 2} .0032637{col 41}{space 1}   -0.61{col 50}{space 3}0.545{col 58}{space 4}-.0083727{col 71}{space 3} .0044206
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0203958{col 30}{space 2} .0329862{col 41}{space 1}    0.62{col 50}{space 3}0.536{col 58}{space 4}-.0442561{col 71}{space 3} .0850476
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2808998{col 30}{space 2} .1125677{col 41}{space 1}    2.50{col 50}{space 3}0.013{col 58}{space 4} .0602712{col 71}{space 3} .5015285
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4428084{col 30}{space 2} .0656437{col 41}{space 1}    6.75{col 50}{space 3}0.000{col 58}{space 4} .3141491{col 71}{space 3} .5714678
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .601696{col 30}{space 2} .0739958{col 41}{space 1}    8.13{col 50}{space 3}0.000{col 58}{space 4} .4566668{col 71}{space 3} .7467252
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0452153{col 30}{space 2}   .05518{col 41}{space 1}    0.82{col 50}{space 3}0.413{col 58}{space 4}-.0629356{col 71}{space 3} .1533661
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3015236{col 30}{space 2} .0571035{col 41}{space 1}    5.28{col 50}{space 3}0.000{col 58}{space 4} .1896027{col 71}{space 3} .4134445
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1198071{col 30}{space 2} .0170128{col 41}{space 1}   -7.04{col 50}{space 3}0.000{col 58}{space 4}-.1531515{col 71}{space 3}-.0864627
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0253327{col 30}{space 2}  .037459{col 41}{space 1}   -0.68{col 50}{space 3}0.499{col 58}{space 4}-.0987509{col 71}{space 3} .0480855
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0470319{col 30}{space 2} .0322499{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0161767{col 71}{space 3} .1102406
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0483065{col 30}{space 2} .0352444{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0207712{col 71}{space 3} .1173842
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.485695{col 30}{space 2} .0833595{col 41}{space 1}   53.81{col 50}{space 3}0.000{col 58}{space 4} 4.322314{col 71}{space 3} 4.649077
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78023597
         {txt}sigma_e {c |} {res} 1.2092564
             {txt}rho {c |} {res} .29393906{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est15
{txt}
{com}. 
. drop pdd9_5
{txt}
{com}. gen pdd9_5= pdd9_vill
{txt}
{com}. xtreg hdd9  pdd9_5 sum_vill  $xlist  pdd9_mean_vill $year_TANZANIA if country==5, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,830
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,710

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0145                                         {txt}min = {res}         1
{txt}     between = {res}0.2294                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1714                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1901.56
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_5 {c |}{col 18}{res}{space 2} .0551174{col 30}{space 2} .0191477{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0175886{col 71}{space 3} .0926461
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0477573{col 30}{space 2} .0070618{col 41}{space 1}   -6.76{col 50}{space 3}0.000{col 58}{space 4}-.0615982{col 71}{space 3}-.0339165
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0016467{col 30}{space 2} .0052974{col 41}{space 1}   -0.31{col 50}{space 3}0.756{col 58}{space 4}-.0120295{col 71}{space 3}  .008736
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0533242{col 30}{space 2} .0656373{col 41}{space 1}    0.81{col 50}{space 3}0.417{col 58}{space 4}-.0753224{col 71}{space 3} .1819709
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0013563{col 30}{space 2} .0010463{col 41}{space 1}   -1.30{col 50}{space 3}0.195{col 58}{space 4}-.0034071{col 71}{space 3} .0006945
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0216875{col 30}{space 2} .0370733{col 41}{space 1}    0.58{col 50}{space 3}0.559{col 58}{space 4}-.0509748{col 71}{space 3} .0943498
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2737777{col 30}{space 2} .0353008{col 41}{space 1}    7.76{col 50}{space 3}0.000{col 58}{space 4} .2045893{col 71}{space 3}  .342966
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2730239{col 30}{space 2} .0864213{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} .1036412{col 71}{space 3} .4424066
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2737047{col 30}{space 2} .0487051{col 41}{space 1}    5.62{col 50}{space 3}0.000{col 58}{space 4} .1782445{col 71}{space 3} .3691649
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0446226{col 30}{space 2} .0561555{col 41}{space 1}    0.79{col 50}{space 3}0.427{col 58}{space 4}-.0654402{col 71}{space 3} .1546854
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .125814{col 30}{space 2} .0387829{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4}  .049801{col 71}{space 3} .2018269
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .231224{col 30}{space 2} .0407079{col 41}{space 1}    5.68{col 50}{space 3}0.000{col 58}{space 4}  .151438{col 71}{space 3}   .31101
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.143467{col 30}{space 2} .0340703{col 41}{space 1}   -4.21{col 50}{space 3}0.000{col 58}{space 4}-.2102436{col 71}{space 3}-.0766904
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0032864{col 30}{space 2} .0030487{col 41}{space 1}    1.08{col 50}{space 3}0.281{col 58}{space 4} -.002689{col 71}{space 3} .0092618
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1223383{col 30}{space 2} .0323731{col 41}{space 1}    3.78{col 50}{space 3}0.000{col 58}{space 4} .0588881{col 71}{space 3} .1857884
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2688533{col 30}{space 2} .1132883{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0468123{col 71}{space 3} .4908942
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .407932{col 30}{space 2} .0664551{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4} .2776825{col 71}{space 3} .5381815
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5547087{col 30}{space 2} .0743284{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .4090277{col 71}{space 3} .7003898
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0113115{col 30}{space 2} .0555256{col 41}{space 1}   -0.20{col 50}{space 3}0.839{col 58}{space 4}-.1201397{col 71}{space 3} .0975166
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2450324{col 30}{space 2} .0573276{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .1326723{col 71}{space 3} .3573925
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0196454{col 30}{space 2}  .023244{col 41}{space 1}   -0.85{col 50}{space 3}0.398{col 58}{space 4}-.0652027{col 71}{space 3}  .025912
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0116127{col 30}{space 2} .0377716{col 41}{space 1}   -0.31{col 50}{space 3}0.759{col 58}{space 4}-.0856438{col 71}{space 3} .0624183
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0292403{col 30}{space 2}  .032572{col 41}{space 1}    0.90{col 50}{space 3}0.369{col 58}{space 4}-.0345997{col 71}{space 3} .0930803
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0855304{col 30}{space 2}  .036549{col 41}{space 1}    2.34{col 50}{space 3}0.019{col 58}{space 4} .0138958{col 71}{space 3}  .157165
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.691372{col 30}{space 2} .1080768{col 41}{space 1}   43.41{col 50}{space 3}0.000{col 58}{space 4} 4.479545{col 71}{space 3} 4.903198
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76283151
         {txt}sigma_e {c |} {res} 1.2279711
             {txt}rho {c |} {res} .27845009{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est25
{txt}
{com}. 
. 
. drop pdd9_5
{txt}
{com}. gen pdd9_5= pdd9_town
{txt}
{com}. xtreg hdd9  pdd9_5 sum_town  $xlist  pdd9_mean_town $year_TANZANIA if country==5, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,830
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,710

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0130                                         {txt}min = {res}         1
{txt}     between = {res}0.2246                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1685                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1860.45
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_5 {c |}{col 18}{res}{space 2}-.0002759{col 30}{space 2} .0209966{col 41}{space 1}   -0.01{col 50}{space 3}0.990{col 58}{space 4}-.0414285{col 71}{space 3} .0408767
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0137397{col 30}{space 2} .0045708{col 41}{space 1}   -3.01{col 50}{space 3}0.003{col 58}{space 4}-.0226982{col 71}{space 3}-.0047812
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0013187{col 30}{space 2} .0052992{col 41}{space 1}   -0.25{col 50}{space 3}0.803{col 58}{space 4}-.0117049{col 71}{space 3} .0090674
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0518961{col 30}{space 2} .0656271{col 41}{space 1}    0.79{col 50}{space 3}0.429{col 58}{space 4}-.0767305{col 71}{space 3} .1805228
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0013316{col 30}{space 2} .0010466{col 41}{space 1}   -1.27{col 50}{space 3}0.203{col 58}{space 4}-.0033829{col 71}{space 3} .0007197
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0213531{col 30}{space 2} .0372256{col 41}{space 1}    0.57{col 50}{space 3}0.566{col 58}{space 4}-.0516078{col 71}{space 3}  .094314
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2786661{col 30}{space 2} .0353176{col 41}{space 1}    7.89{col 50}{space 3}0.000{col 58}{space 4} .2094448{col 71}{space 3} .3478873
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2617608{col 30}{space 2} .0864074{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .0924055{col 71}{space 3} .4311161
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2716899{col 30}{space 2} .0487689{col 41}{space 1}    5.57{col 50}{space 3}0.000{col 58}{space 4} .1761045{col 71}{space 3} .3672752
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0222286{col 30}{space 2} .0560658{col 41}{space 1}    0.40{col 50}{space 3}0.692{col 58}{space 4}-.0876584{col 71}{space 3} .1321155
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1316793{col 30}{space 2} .0388549{col 41}{space 1}    3.39{col 50}{space 3}0.001{col 58}{space 4} .0555251{col 71}{space 3} .2078335
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2353328{col 30}{space 2} .0407219{col 41}{space 1}    5.78{col 50}{space 3}0.000{col 58}{space 4} .1555193{col 71}{space 3} .3151463
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1536899{col 30}{space 2} .0340438{col 41}{space 1}   -4.51{col 50}{space 3}0.000{col 58}{space 4}-.2204146{col 71}{space 3}-.0869652
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0039266{col 30}{space 2} .0030548{col 41}{space 1}    1.29{col 50}{space 3}0.199{col 58}{space 4}-.0020607{col 71}{space 3}  .009914
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1350928{col 30}{space 2} .0325499{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4} .0712962{col 71}{space 3} .1988893
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2803462{col 30}{space 2} .1138401{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4} .0572237{col 71}{space 3} .5034687
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3996568{col 30}{space 2} .0666283{col 41}{space 1}    6.00{col 50}{space 3}0.000{col 58}{space 4} .2690677{col 71}{space 3} .5302458
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5565236{col 30}{space 2}  .074552{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .4104043{col 71}{space 3} .7026428
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0058507{col 30}{space 2}  .055638{col 41}{space 1}   -0.11{col 50}{space 3}0.916{col 58}{space 4}-.1148992{col 71}{space 3} .1031978
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2576935{col 30}{space 2} .0574076{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .1451768{col 71}{space 3} .3702103
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0119884{col 30}{space 2} .0251349{col 41}{space 1}    0.48{col 50}{space 3}0.633{col 58}{space 4}-.0372751{col 71}{space 3} .0612519
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0169396{col 30}{space 2} .0376636{col 41}{space 1}    0.45{col 50}{space 3}0.653{col 58}{space 4}-.0568796{col 71}{space 3} .0907589
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0556129{col 30}{space 2} .0331047{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4}-.0092712{col 71}{space 3}  .120497
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0421274{col 30}{space 2} .0356936{col 41}{space 1}    1.18{col 50}{space 3}0.238{col 58}{space 4}-.0278308{col 71}{space 3} .1120856
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.667922{col 30}{space 2} .1149119{col 41}{space 1}   40.62{col 50}{space 3}0.000{col 58}{space 4} 4.442699{col 71}{space 3} 4.893145
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76536734
         {txt}sigma_e {c |} {res} 1.2283347
             {txt}rho {c |} {res}  .2796663{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est35
{txt}
{com}. 
. 
. drop pdd9_5
{txt}
{com}. gen pdd9_5= pdd9_dist
{txt}
{com}. xtreg hdd9  pdd9_5 sum_dist  $xlist  pdd9_mean_dist $year_TANZANIA if country==5, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,830
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,710

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0139                                         {txt}min = {res}         1
{txt}     between = {res}0.2238                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1683                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1841.23
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_5 {c |}{col 18}{res}{space 2}-.0348218{col 30}{space 2} .0263021{col 41}{space 1}   -1.32{col 50}{space 3}0.186{col 58}{space 4}-.0863731{col 71}{space 3} .0167294
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0010149{col 30}{space 2} .0010743{col 41}{space 1}    0.94{col 50}{space 3}0.345{col 58}{space 4}-.0010907{col 71}{space 3} .0031204
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0013754{col 30}{space 2}  .005311{col 41}{space 1}   -0.26{col 50}{space 3}0.796{col 58}{space 4}-.0117847{col 71}{space 3}  .009034
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0512644{col 30}{space 2} .0656109{col 41}{space 1}    0.78{col 50}{space 3}0.435{col 58}{space 4}-.0773306{col 71}{space 3} .1798594
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0011826{col 30}{space 2} .0010481{col 41}{space 1}   -1.13{col 50}{space 3}0.259{col 58}{space 4}-.0032368{col 71}{space 3} .0008716
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0261261{col 30}{space 2} .0372185{col 41}{space 1}    0.70{col 50}{space 3}0.483{col 58}{space 4}-.0468209{col 71}{space 3} .0990731
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .278076{col 30}{space 2}  .035345{col 41}{space 1}    7.87{col 50}{space 3}0.000{col 58}{space 4}  .208801{col 71}{space 3} .3473509
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2557324{col 30}{space 2} .0864844{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .0862262{col 71}{space 3} .4252386
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2726461{col 30}{space 2} .0487599{col 41}{space 1}    5.59{col 50}{space 3}0.000{col 58}{space 4} .1770784{col 71}{space 3} .3682137
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0325489{col 30}{space 2} .0560783{col 41}{space 1}    0.58{col 50}{space 3}0.562{col 58}{space 4}-.0773625{col 71}{space 3} .1424603
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1300051{col 30}{space 2} .0388652{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .0538307{col 71}{space 3} .2061795
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2345506{col 30}{space 2} .0406673{col 41}{space 1}    5.77{col 50}{space 3}0.000{col 58}{space 4} .1548441{col 71}{space 3}  .314257
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1548711{col 30}{space 2} .0340538{col 41}{space 1}   -4.55{col 50}{space 3}0.000{col 58}{space 4}-.2216154{col 71}{space 3}-.0881268
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0029692{col 30}{space 2} .0030479{col 41}{space 1}    0.97{col 50}{space 3}0.330{col 58}{space 4}-.0030045{col 71}{space 3} .0089429
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1213342{col 30}{space 2} .0322537{col 41}{space 1}    3.76{col 50}{space 3}0.000{col 58}{space 4} .0581182{col 71}{space 3} .1845502
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2791305{col 30}{space 2} .1139429{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0558065{col 71}{space 3} .5024545
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4097653{col 30}{space 2} .0664276{col 41}{space 1}    6.17{col 50}{space 3}0.000{col 58}{space 4} .2795696{col 71}{space 3}  .539961
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5736707{col 30}{space 2} .0739148{col 41}{space 1}    7.76{col 50}{space 3}0.000{col 58}{space 4} .4288004{col 71}{space 3} .7185411
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0057067{col 30}{space 2} .0555978{col 41}{space 1}   -0.10{col 50}{space 3}0.918{col 58}{space 4}-.1146763{col 71}{space 3}  .103263
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2516718{col 30}{space 2} .0574227{col 41}{space 1}    4.38{col 50}{space 3}0.000{col 58}{space 4} .1391254{col 71}{space 3} .3642183
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0873343{col 30}{space 2} .0337592{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0211676{col 71}{space 3} .1535011
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0302565{col 30}{space 2} .0379631{col 41}{space 1}    0.80{col 50}{space 3}0.425{col 58}{space 4}-.0441498{col 71}{space 3} .1046627
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0312097{col 30}{space 2} .0339707{col 41}{space 1}    0.92{col 50}{space 3}0.358{col 58}{space 4}-.0353717{col 71}{space 3}  .097791
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0551242{col 30}{space 2} .0358309{col 41}{space 1}    1.54{col 50}{space 3}0.124{col 58}{space 4}-.0151031{col 71}{space 3} .1253515
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.214838{col 30}{space 2} .1676226{col 41}{space 1}   25.14{col 50}{space 3}0.000{col 58}{space 4} 3.886304{col 71}{space 3} 4.543372
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76782572
         {txt}sigma_e {c |} {res} 1.2278813
             {txt}rho {c |} {res} .28110939{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est45
{txt}
{com}. 
. 
. 
. *Uganda
. gen pdd9_4=pdd9
{txt}
{com}. xtreg hdd9  pdd9_4   $xlist  pdd9_mean $year_UGANDA if country==4, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,114
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,402

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0485                                         {txt}min = {res}         1
{txt}     between = {res}0.2727                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1902                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  2532.02
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_4 {c |}{col 18}{res}{space 2} .0994732{col 30}{space 2} .0113779{col 41}{space 1}    8.74{col 50}{space 3}0.000{col 58}{space 4} .0771729{col 71}{space 3} .1217735
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0118347{col 30}{space 2} .0055723{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0009131{col 71}{space 3} .0227563
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0639706{col 30}{space 2} .0594067{col 41}{space 1}    1.08{col 50}{space 3}0.282{col 58}{space 4}-.0524644{col 71}{space 3} .1804056
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0012154{col 30}{space 2} .0010263{col 41}{space 1}   -1.18{col 50}{space 3}0.236{col 58}{space 4} -.003227{col 71}{space 3} .0007962
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .058616{col 30}{space 2} .0344209{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0088478{col 71}{space 3} .1260798
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3265784{col 30}{space 2} .0337857{col 41}{space 1}    9.67{col 50}{space 3}0.000{col 58}{space 4} .2603596{col 71}{space 3} .3927972
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2298902{col 30}{space 2}   .05619{col 41}{space 1}    4.09{col 50}{space 3}0.000{col 58}{space 4} .1197599{col 71}{space 3} .3400205
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2447202{col 30}{space 2} .0373205{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .1715733{col 71}{space 3} .3178671
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3422081{col 30}{space 2} .0378166{col 41}{space 1}    9.05{col 50}{space 3}0.000{col 58}{space 4} .2680889{col 71}{space 3} .4163273
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0415031{col 30}{space 2} .0304786{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.0182339{col 71}{space 3} .1012401
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1958873{col 30}{space 2} .0320586{col 41}{space 1}    6.11{col 50}{space 3}0.000{col 58}{space 4} .1330536{col 71}{space 3}  .258721
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0152503{col 30}{space 2} .0250389{col 41}{space 1}   -0.61{col 50}{space 3}0.542{col 58}{space 4}-.0643256{col 71}{space 3}  .033825
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0002386{col 30}{space 2} .0016131{col 41}{space 1}    0.15{col 50}{space 3}0.882{col 58}{space 4}-.0029231{col 71}{space 3} .0034002
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0167297{col 30}{space 2} .0279384{col 41}{space 1}    0.60{col 50}{space 3}0.549{col 58}{space 4}-.0380284{col 71}{space 3} .0714879
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1441942{col 30}{space 2} .0874612{col 41}{space 1}    1.65{col 50}{space 3}0.099{col 58}{space 4}-.0272267{col 71}{space 3} .3156151
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3742288{col 30}{space 2} .0625765{col 41}{space 1}    5.98{col 50}{space 3}0.000{col 58}{space 4} .2515812{col 71}{space 3} .4968764
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4300925{col 30}{space 2} .0697059{col 41}{space 1}    6.17{col 50}{space 3}0.000{col 58}{space 4} .2934714{col 71}{space 3} .5667136
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .178564{col 30}{space 2} .0559109{col 41}{space 1}    3.19{col 50}{space 3}0.001{col 58}{space 4} .0689806{col 71}{space 3} .2881474
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3427401{col 30}{space 2} .0543074{col 41}{space 1}    6.31{col 50}{space 3}0.000{col 58}{space 4} .2362995{col 71}{space 3} .4491808
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0239568{col 30}{space 2} .0173747{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4} -.010097{col 71}{space 3} .0580106
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1296924{col 30}{space 2} .0382397{col 41}{space 1}   -3.39{col 50}{space 3}0.001{col 58}{space 4}-.2046409{col 71}{space 3} -.054744
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0485443{col 30}{space 2} .0333045{col 41}{space 1}   -1.46{col 50}{space 3}0.145{col 58}{space 4}  -.11382{col 71}{space 3} .0167313
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3397759{col 30}{space 2} .0338467{col 41}{space 1}   10.04{col 50}{space 3}0.000{col 58}{space 4} .2734376{col 71}{space 3} .4061143
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0846579{col 30}{space 2} .0339696{col 41}{space 1}    2.49{col 50}{space 3}0.013{col 58}{space 4} .0180786{col 71}{space 3} .1512372
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2929945{col 30}{space 2} .0321095{col 41}{space 1}    9.12{col 50}{space 3}0.000{col 58}{space 4} .2300611{col 71}{space 3}  .355928
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.866225{col 30}{space 2} .0883898{col 41}{space 1}   43.74{col 50}{space 3}0.000{col 58}{space 4} 3.692984{col 71}{space 3} 4.039466
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .81142007
         {txt}sigma_e {c |} {res} 1.2635858
             {txt}rho {c |} {res} .29196783{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est16
{txt}
{com}. 
. drop pdd9_4
{txt}
{com}. gen pdd9_4= pdd9_vill
{txt}
{com}. xtreg hdd9  pdd9_4 sum_vill  $xlist  pdd9_mean_vill $year_UGANDA if country==4, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,114
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,402

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0420                                         {txt}min = {res}         1
{txt}     between = {res}0.2855                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1916                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2534.12
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_4 {c |}{col 18}{res}{space 2} .0199183{col 30}{space 2} .0133128{col 41}{space 1}    1.50{col 50}{space 3}0.135{col 58}{space 4}-.0061743{col 71}{space 3}  .046011
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2} -.030819{col 30}{space 2} .0047062{col 41}{space 1}   -6.55{col 50}{space 3}0.000{col 58}{space 4} -.040043{col 71}{space 3}-.0215951
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .025645{col 30}{space 2} .0054645{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0149347{col 71}{space 3} .0363552
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0531743{col 30}{space 2} .0602836{col 41}{space 1}    0.88{col 50}{space 3}0.378{col 58}{space 4}-.0649794{col 71}{space 3}  .171328
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0010848{col 30}{space 2} .0010181{col 41}{space 1}   -1.07{col 50}{space 3}0.287{col 58}{space 4}-.0030803{col 71}{space 3} .0009107
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}   .04709{col 30}{space 2} .0343335{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0202025{col 71}{space 3} .1143825
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3243791{col 30}{space 2} .0337351{col 41}{space 1}    9.62{col 50}{space 3}0.000{col 58}{space 4} .2582594{col 71}{space 3} .3904987
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2354538{col 30}{space 2} .0563473{col 41}{space 1}    4.18{col 50}{space 3}0.000{col 58}{space 4} .1250151{col 71}{space 3} .3458925
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2496645{col 30}{space 2} .0374903{col 41}{space 1}    6.66{col 50}{space 3}0.000{col 58}{space 4} .1761848{col 71}{space 3} .3231441
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}    .3365{col 30}{space 2} .0378888{col 41}{space 1}    8.88{col 50}{space 3}0.000{col 58}{space 4} .2622394{col 71}{space 3} .4107607
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0370737{col 30}{space 2} .0305793{col 41}{space 1}    1.21{col 50}{space 3}0.225{col 58}{space 4}-.0228607{col 71}{space 3}  .097008
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2046684{col 30}{space 2} .0321477{col 41}{space 1}    6.37{col 50}{space 3}0.000{col 58}{space 4} .1416599{col 71}{space 3} .2676768
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0092233{col 30}{space 2} .0249723{col 41}{space 1}    0.37{col 50}{space 3}0.712{col 58}{space 4}-.0397216{col 71}{space 3} .0581681
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0016156{col 30}{space 2} .0017395{col 41}{space 1}    0.93{col 50}{space 3}0.353{col 58}{space 4}-.0017937{col 71}{space 3} .0050249
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0508888{col 30}{space 2} .0277693{col 41}{space 1}    1.83{col 50}{space 3}0.067{col 58}{space 4} -.003538{col 71}{space 3} .1053156
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1395907{col 30}{space 2} .0870131{col 41}{space 1}    1.60{col 50}{space 3}0.109{col 58}{space 4}-.0309519{col 71}{space 3} .3101333
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3471975{col 30}{space 2}  .062166{col 41}{space 1}    5.59{col 50}{space 3}0.000{col 58}{space 4} .2253545{col 71}{space 3} .4690405
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3740562{col 30}{space 2} .0688118{col 41}{space 1}    5.44{col 50}{space 3}0.000{col 58}{space 4} .2391875{col 71}{space 3} .5089249
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1121482{col 30}{space 2} .0551921{col 41}{space 1}    2.03{col 50}{space 3}0.042{col 58}{space 4} .0039737{col 71}{space 3} .2203226
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3036198{col 30}{space 2} .0536368{col 41}{space 1}    5.66{col 50}{space 3}0.000{col 58}{space 4} .1984935{col 71}{space 3}  .408746
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1852284{col 30}{space 2} .0217363{col 41}{space 1}    8.52{col 50}{space 3}0.000{col 58}{space 4}  .142626{col 71}{space 3} .2278308
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1259459{col 30}{space 2} .0384392{col 41}{space 1}   -3.28{col 50}{space 3}0.001{col 58}{space 4}-.2012854{col 71}{space 3}-.0506065
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0407199{col 30}{space 2} .0340009{col 41}{space 1}   -1.20{col 50}{space 3}0.231{col 58}{space 4}-.1073604{col 71}{space 3} .0259206
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3514356{col 30}{space 2} .0346141{col 41}{space 1}   10.15{col 50}{space 3}0.000{col 58}{space 4} .2835932{col 71}{space 3}  .419278
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1041186{col 30}{space 2} .0343085{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .0368752{col 71}{space 3}  .171362
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2975213{col 30}{space 2} .0320754{col 41}{space 1}    9.28{col 50}{space 3}0.000{col 58}{space 4} .2346547{col 71}{space 3}  .360388
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.277769{col 30}{space 2}  .127035{col 41}{space 1}   25.80{col 50}{space 3}0.000{col 58}{space 4} 3.028785{col 71}{space 3} 3.526753
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .79554545
         {txt}sigma_e {c |} {res} 1.2677833
             {txt}rho {c |} {res} .28252027{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est26
{txt}
{com}. 
. 
. drop pdd9_4
{txt}
{com}. gen pdd9_4= pdd9_town
{txt}
{com}. xtreg hdd9  pdd9_4 sum_town  $xlist  pdd9_mean_town $year_UGANDA if country==4, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,114
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,402

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0421                                         {txt}min = {res}         1
{txt}     between = {res}0.2808                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1912                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2522.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_4 {c |}{col 18}{res}{space 2} .0147563{col 30}{space 2} .0138797{col 41}{space 1}    1.06{col 50}{space 3}0.288{col 58}{space 4}-.0124474{col 71}{space 3} .0419599
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0170732{col 30}{space 2} .0031232{col 41}{space 1}   -5.47{col 50}{space 3}0.000{col 58}{space 4}-.0231947{col 71}{space 3}-.0109518
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0256898{col 30}{space 2} .0054808{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0149477{col 71}{space 3}  .036432
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0502369{col 30}{space 2}  .060326{col 41}{space 1}    0.83{col 50}{space 3}0.405{col 58}{space 4}-.0679999{col 71}{space 3} .1684738
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0007696{col 30}{space 2} .0010178{col 41}{space 1}   -0.76{col 50}{space 3}0.450{col 58}{space 4}-.0027645{col 71}{space 3} .0012253
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0461251{col 30}{space 2} .0343732{col 41}{space 1}    1.34{col 50}{space 3}0.180{col 58}{space 4} -.021245{col 71}{space 3} .1134953
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .322941{col 30}{space 2} .0338457{col 41}{space 1}    9.54{col 50}{space 3}0.000{col 58}{space 4} .2566045{col 71}{space 3} .3892774
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2373777{col 30}{space 2} .0564838{col 41}{space 1}    4.20{col 50}{space 3}0.000{col 58}{space 4} .1266714{col 71}{space 3} .3480839
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .252401{col 30}{space 2} .0374712{col 41}{space 1}    6.74{col 50}{space 3}0.000{col 58}{space 4} .1789588{col 71}{space 3} .3258432
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3421277{col 30}{space 2} .0379251{col 41}{space 1}    9.02{col 50}{space 3}0.000{col 58}{space 4} .2677959{col 71}{space 3} .4164594
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0359025{col 30}{space 2} .0305756{col 41}{space 1}    1.17{col 50}{space 3}0.240{col 58}{space 4}-.0240245{col 71}{space 3} .0958295
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .202562{col 30}{space 2} .0321543{col 41}{space 1}    6.30{col 50}{space 3}0.000{col 58}{space 4} .1395407{col 71}{space 3} .2655833
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0063968{col 30}{space 2} .0250238{col 41}{space 1}    0.26{col 50}{space 3}0.798{col 58}{space 4} -.042649{col 71}{space 3} .0554426
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0015702{col 30}{space 2} .0017172{col 41}{space 1}    0.91{col 50}{space 3}0.360{col 58}{space 4}-.0017953{col 71}{space 3} .0049358
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0503895{col 30}{space 2} .0277635{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.0040259{col 71}{space 3} .1048049
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1402172{col 30}{space 2} .0870363{col 41}{space 1}    1.61{col 50}{space 3}0.107{col 58}{space 4}-.0303709{col 71}{space 3} .3108053
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3463817{col 30}{space 2} .0621399{col 41}{space 1}    5.57{col 50}{space 3}0.000{col 58}{space 4} .2245897{col 71}{space 3} .4681737
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3752667{col 30}{space 2} .0689561{col 41}{space 1}    5.44{col 50}{space 3}0.000{col 58}{space 4} .2401153{col 71}{space 3} .5104181
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1162884{col 30}{space 2} .0553467{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4} .0078108{col 71}{space 3} .2247659
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3110433{col 30}{space 2} .0537298{col 41}{space 1}    5.79{col 50}{space 3}0.000{col 58}{space 4} .2057347{col 71}{space 3} .4163518
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1898021{col 30}{space 2} .0226143{col 41}{space 1}    8.39{col 50}{space 3}0.000{col 58}{space 4} .1454789{col 71}{space 3} .2341253
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1348144{col 30}{space 2} .0382795{col 41}{space 1}   -3.52{col 50}{space 3}0.000{col 58}{space 4}-.2098409{col 71}{space 3}-.0597879
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0482929{col 30}{space 2} .0339705{col 41}{space 1}   -1.42{col 50}{space 3}0.155{col 58}{space 4}-.1148738{col 71}{space 3} .0182881
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3564511{col 30}{space 2} .0346482{col 41}{space 1}   10.29{col 50}{space 3}0.000{col 58}{space 4} .2885419{col 71}{space 3} .4243604
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}  .107944{col 30}{space 2} .0344977{col 41}{space 1}    3.13{col 50}{space 3}0.002{col 58}{space 4} .0403297{col 71}{space 3} .1755584
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2933185{col 30}{space 2} .0321388{col 41}{space 1}    9.13{col 50}{space 3}0.000{col 58}{space 4} .2303276{col 71}{space 3} .3563095
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.142159{col 30}{space 2} .1307944{col 41}{space 1}   24.02{col 50}{space 3}0.000{col 58}{space 4} 2.885807{col 71}{space 3} 3.398511
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80192163
         {txt}sigma_e {c |} {res} 1.2678475
             {txt}rho {c |} {res} .28574709{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est36
{txt}
{com}. 
. 
. drop pdd9_4
{txt}
{com}. gen pdd9_4= pdd9_dist
{txt}
{com}. xtreg hdd9  pdd9_4 sum_dist  $xlist  pdd9_mean_dist $year_UGANDA if country==4, cluster (HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,114
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,402

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0424                                         {txt}min = {res}         1
{txt}     between = {res}0.2765                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1892                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2415.31
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pdd9_4 {c |}{col 18}{res}{space 2} .0149778{col 30}{space 2} .0171948{col 41}{space 1}    0.87{col 50}{space 3}0.384{col 58}{space 4}-.0187234{col 71}{space 3}  .048679
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0001254{col 30}{space 2} .0009542{col 41}{space 1}    0.13{col 50}{space 3}0.895{col 58}{space 4}-.0017447{col 71}{space 3} .0019956
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0300247{col 30}{space 2} .0054889{col 41}{space 1}    5.47{col 50}{space 3}0.000{col 58}{space 4} .0192667{col 71}{space 3} .0407828
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0569559{col 30}{space 2}  .060222{col 41}{space 1}    0.95{col 50}{space 3}0.344{col 58}{space 4} -.061077{col 71}{space 3} .1749888
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0007224{col 30}{space 2}  .001022{col 41}{space 1}   -0.71{col 50}{space 3}0.480{col 58}{space 4}-.0027255{col 71}{space 3} .0012808
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0350735{col 30}{space 2}  .034418{col 41}{space 1}    1.02{col 50}{space 3}0.308{col 58}{space 4}-.0323845{col 71}{space 3} .1025315
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .317831{col 30}{space 2} .0338328{col 41}{space 1}    9.39{col 50}{space 3}0.000{col 58}{space 4} .2515199{col 71}{space 3} .3841422
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2364591{col 30}{space 2} .0563699{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .1259761{col 71}{space 3} .3469421
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2487883{col 30}{space 2} .0374789{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4}  .175331{col 71}{space 3} .3222456
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3407008{col 30}{space 2} .0379529{col 41}{space 1}    8.98{col 50}{space 3}0.000{col 58}{space 4} .2663144{col 71}{space 3} .4150871
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0359354{col 30}{space 2} .0305883{col 41}{space 1}    1.17{col 50}{space 3}0.240{col 58}{space 4}-.0240166{col 71}{space 3} .0958873
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2020548{col 30}{space 2} .0321562{col 41}{space 1}    6.28{col 50}{space 3}0.000{col 58}{space 4} .1390299{col 71}{space 3} .2650797
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0244943{col 30}{space 2} .0250646{col 41}{space 1}    0.98{col 50}{space 3}0.328{col 58}{space 4}-.0246314{col 71}{space 3}   .07362
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0024588{col 30}{space 2} .0018195{col 41}{space 1}    1.35{col 50}{space 3}0.177{col 58}{space 4}-.0011074{col 71}{space 3} .0060249
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0654561{col 30}{space 2} .0277929{col 41}{space 1}    2.36{col 50}{space 3}0.019{col 58}{space 4}  .010983{col 71}{space 3} .1199292
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1259603{col 30}{space 2} .0870294{col 41}{space 1}    1.45{col 50}{space 3}0.148{col 58}{space 4}-.0446141{col 71}{space 3} .2965348
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3358245{col 30}{space 2} .0625471{col 41}{space 1}    5.37{col 50}{space 3}0.000{col 58}{space 4} .2132344{col 71}{space 3} .4584145
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3145981{col 30}{space 2} .0690216{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .1793183{col 71}{space 3} .4498779
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0727587{col 30}{space 2} .0555769{col 41}{space 1}    1.31{col 50}{space 3}0.190{col 58}{space 4}-.0361699{col 71}{space 3} .1816874
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2914896{col 30}{space 2} .0536726{col 41}{space 1}    5.43{col 50}{space 3}0.000{col 58}{space 4} .1862934{col 71}{space 3} .3966859
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .2106741{col 30}{space 2}  .029668{col 41}{space 1}    7.10{col 50}{space 3}0.000{col 58}{space 4} .1525258{col 71}{space 3} .2688223
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1398641{col 30}{space 2} .0384604{col 41}{space 1}   -3.64{col 50}{space 3}0.000{col 58}{space 4}-.2152451{col 71}{space 3}-.0644831
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0553303{col 30}{space 2} .0343198{col 41}{space 1}   -1.61{col 50}{space 3}0.107{col 58}{space 4}-.1225958{col 71}{space 3} .0119353
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3402228{col 30}{space 2} .0346634{col 41}{space 1}    9.82{col 50}{space 3}0.000{col 58}{space 4} .2722837{col 71}{space 3} .4081618
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0938754{col 30}{space 2} .0345239{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0262097{col 71}{space 3}  .161541
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2852875{col 30}{space 2} .0323152{col 41}{space 1}    8.83{col 50}{space 3}0.000{col 58}{space 4}  .221951{col 71}{space 3} .3486241
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.615979{col 30}{space 2} .1818335{col 41}{space 1}   14.39{col 50}{space 3}0.000{col 58}{space 4} 2.259592{col 71}{space 3} 2.972366
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80655393
         {txt}sigma_e {c |} {res} 1.2676197
             {txt}rho {c |} {res} .28817773{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est46
{txt}
{com}. 
. 
. 
. 
. coefplot (est1, label("Farm-level production diversity") msymbol(d) mfcolor(white) mlcolor(red)   ) (est2, label("") msymbol(s) mlcolor(navy) mfcolor(white))  (est3, label("") msymbol(o) mlcolor(orange) mfcolor(white))  (est4, label("") msymbol(t) mlcolor(green) mfcolor(white)) ///
> (est11, label("")  msymbol(d) mfcolor(white) mlcolor(red)) (est21, label("Village-level production diversity")  msymbol(s) mcolor(navy) mfcolor(white))  (est31,  label("") msymbol(o) mlcolor(orange) mfcolor(white))  (est41,  label("")  msymbol(t) mlcolor(green) mfcolor(white)) ///  
> (est12, label("")  msymbol(d) mfcolor(white) mlcolor(red)) (est22, label("")  msymbol(s) mcolor(navy) mfcolor(white))  (est32,  label("Town-level production diversity") msymbol(o) mlcolor(orange) mfcolor(white))  (est42,  label("") msymbol(t) mlcolor(green) mfcolor(white)) ///  
> (est13, label("")  msymbol(d) mfcolor(white) mlcolor(red)) (est23, label("")  msymbol(s) mcolor(navy) mfcolor(white))  (est33,  label("") msymbol(o) mlcolor(orange) mfcolor(white))  (est43,  label("District-level production diversity") msymbol(t) mlcolor(green) mfcolor(white)) ///  
> (est14, label("")  msymbol(d) mfcolor(white) mlcolor(red)) (est24, label("")  msymbol(s) mcolor(navy) mfcolor(white))  (est34,  label("") msymbol(o) mlcolor(orange) mfcolor(white))  (est44,  label("") msymbol(t) mlcolor(green) mfcolor(white)) ///  
> (est15, label("")  msymbol(d) mfcolor(white) mlcolor(red)) (est25, label("")  msymbol(s) mcolor(navy) mfcolor(white))  (est35,  label("") msymbol(o) mlcolor(orange) mfcolor(white))  (est45,  label("") msymbol(t) mlcolor(green) mfcolor(white)) ///  
> (est16, label("")  msymbol(d) mfcolor(white) mlcolor(red)) (est26, label("")  msymbol(s) mcolor(navy) mfcolor(white))  (est36,  label("") msymbol(o) mlcolor(orange) mfcolor(white))  (est46,  label("") msymbol(t) mlcolor(green) mfcolor(white)) ///  
> ,  keep(pdd9_whole pdd9_1 pdd9_2 pdd9_3  pdd9_4 pdd9_5 pdd9_6) vertical ciopts(lcolor(black%10) recast(rcap))  ///
> legend( size(small) rows(3) nobox region(color(ltbluishgray) lstyle(none))) ///  
>   ytitle("HDDS", size(small)) levels(95) xmtick(0.6 1.6 2.8 4 5.1 6.2 7.4) xlabel( 0.6 "All countries" 1.6 "Ethiopia" 2.8 "Malawi" 4 "Niger"    5.1 "Nigeria" 6.2 "Tanzania" 7.4 "Uganda", labsize(small)) xscale(r(0(0.5)3.5)) ylabel(-0.1 0 0.1 0.2 0.3) ymtick(-0.1 0 0.1 0.2 0.3)
{res}{p 0 4 2}
{txt}(note:  named style
p16 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p16 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p17 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p17 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p18 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p18 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p19 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p19 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p20 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p20 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p21 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p21 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p22 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p22 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p23 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p23 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p24 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p24 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p25 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p25 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p26 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p26 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p27 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p27 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p28 not found in class
seriesstyle,  default attributes used)
{p_end}
{p 0 4 2}
{txt}(note:  named style
p28 not found in class
seriesstyle,  default attributes used)
{p_end}
{res}{txt}
{com}.   graph save "Figure_4.gph", replace
{res}{txt}(file Figure_4.gph saved)

{com}. 
. restore
{txt}
{com}. 
. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                            Figure 3b                                         *
. ********************************************************************************
. drop if own_value_share==.
{txt}(11,739 observations deleted)

{com}. gen subsistence=1 if own_value_share>0.50&own_value_share<.
{txt}(52,058 missing values generated)

{com}. replace subsistence=0 if own_value_share<=0.50
{txt}(52,058 real changes made)

{com}. 
. preserve
{txt}
{com}. collapse (mean) hdd9 pdd9, by(subsistence) 
{txt}
{com}. save whole_sample_graph_subsistence, replace
{txt}file whole_sample_graph_subsistence.dta saved

{com}. restore
{txt}
{com}. 
. collapse (mean) hdd9 pdd9, by(country subsistence) 
{txt}
{com}. append using whole_sample_graph_subsistence
{txt}
{com}. 
. 
. gen country_new=1 if country==3
{txt}(12 missing values generated)

{com}. replace country_new=2 if country==6
{txt}(2 real changes made)

{com}. replace country_new=3 if country==1
{txt}(2 real changes made)

{com}. replace country_new=4 if country==2
{txt}(2 real changes made)

{com}. replace country_new=5 if country==5
{txt}(2 real changes made)

{com}. replace country_new=6 if country==4
{txt}(2 real changes made)

{com}. drop country
{txt}
{com}. gen country=country_new
{txt}(2 missing values generated)

{com}. 
. replace country=0 if country==.
{txt}(2 real changes made)

{com}. gen country_1=country-0.3
{txt}
{com}. gen country_2=country
{txt}
{com}. 
. twoway bar hdd9 country_1 if subsistence==0, barw(0.3)  color(navy%80) || scatter  pdd9 country_1 if subsistence==0, msymbol(S) mfcolor(white) mlcolor(red)||bar hdd9 country_2 if subsistence==1, barw(0.3)  color(red%50)   || scatter  pdd9 country_2 if subsistence==1, msymbol(D) mfcolor(white) mlcolor(navy) ///
>  xlabel(-0.15 "All countries" 0.85 "Ethiopia" 1.85 "Malawi" 2.85 "Niger" 3.85 "Nigeria" 4.85 "Tanzania" 5.85 "Uganda", labsize(small)) xmtick(-0.15 0.85 1.85 2.85 3.85 4.85 5.85) ytitle("Diversity Score", size(small)) plotregion(margin(0)) ymtick(0(1)9) ylabel(0 1 2 3 4 5 6 )   ///
>   leg(on order(1 2 3 4)  label(1 "HDDS among non-subsistence households")label(2 "FPD among non-subsistence households" ) label(3 "HDDS among subsistence households" ) label(4 "FPD among subsistence households" ) col(2) ring(5) pos(6) size(vsmall) )
{p 0 4 2}
{txt}(note:  named style
0 not found in class
margin,  default attributes used)
{p_end}
{res}{txt}
{com}.   graph save "Figure_3b.gph", replace
{res}{txt}(file Figure_3b.gph saved)

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\lSMS ISA\dofile\Submission\Table1_Figures.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 5 Apr 2024, 10:59:38
{txt}{.-}
{smcl}
{txt}{sf}{ul off}